Digital readiness in Nigerian midwifery education: a mixed-methods study of 19 training institutions

Digital readiness in Nigerian midwifery education: a mixed-methods study of 19 training institutions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Digital readiness in Nigerian midwifery education: a mixed-methods study of 19 training institutions Halima Musa Abdul, Hauwa Mohammed, Alice Norah Ladur, Sarah White, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9085369/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background Digital transformation in health professions education is often framed as a matter of technology adoption and educator attitudes. However, in low-resource settings, institutional enabling conditions may play a more decisive role in determining whether digital tools can be meaningfully integrated into teaching practice. This study assessed digital teaching readiness in pre-service midwifery institutions in Nigeria and examined how structural capacity shapes the adoption of digital technologies in education. Methods A convergent parallel mixed-methods design was used. Nineteen midwifery training institutions across five geopolitical zones were assessed using a structured institutional checklist administered electronically via REDCap. Qualitative data included 13 in-depth interviews with educators and preceptors, three focus group discussions with 25 students, and 37 teaching observations. A Digital Teaching Readiness Index (DTRI; 0–100) was constructed from five components: student Internet access, computer laboratories/library computers, projector availability, learning management system (LMS) use, and observed ICT use during teaching. Quantitative data were analysed descriptively, and associations between student–educator ratios and DTRI scores were explored using Spearman rank correlation. Qualitative data were analysed thematically. Results Digital infrastructure was limited. Five institutions (26.3%) provided student Internet access, eight (42.1%) had functional computer laboratories/library computers, and one (5.3%) reported LMS use. ICT use was observed in 6 of 37 teaching sessions (16.2%). DTRI scores ranged from 0 to 60: eleven institutions (57.9%) scored < 20, two (10.5%) scored 20–39, and six (31.6%) scored 40–60. Student–educator ratios varied widely (8:1–282:1) and were moderately negatively correlated with DTRI scores (ρ ≈ −0.58). Qualitative findings highlighted unreliable electricity, limited equipment, and funding constraints as key barriers to digital implementation. Conclusions Digital integration in Nigerian midwifery education is constrained less by attitudinal resistance than by institutional capacity limitations. Addressing infrastructure, governance alignment, and educator support is critical for sustainable digital adoption. The DTRI provides a practical benchmarking tool for assessing digital readiness in similar low-resource training environments. Digital technology midwifery education e-learning mixed methods Nigeria health workforce training Digital Teaching Readiness Index Introduction The rise of digital technology has significantly transformed education globally, prompting institutions to adopt technology-driven approaches that differ from conventional methods [ 1 , 2 ]. This shift has reshaped teaching practices in nursing and midwifery, where effective digital integration has become central to delivering scalable, competency-based education. Digital approaches can support the development of core midwifery competencies by enhancing access to learning resources, facilitating interactive teaching, and complementing clinical training [ 3 ]. Nurse and midwife educators are increasingly expected to demonstrate digital competence to enhance learning, support student engagement, and maintain pedagogical effectiveness [ 4 , 5 ]. Digital education uses web-based technologies to support flexible and interactive learning, either fully online or blended with face-to-face instruction [ 6 , 7 ]. Therefore digital learning can enhance engagement, access, and clinical competence, particularly in resource-constrained settings [ 3 , 8 , 9 ]. Equipping midwifery students with digital competencies is increasingly viewed as essential for sustaining quality and innovation in pre-service training [ 10 , 11 ]. Global midwifery education frameworks emphasise the importance of adequate educator capacity to support competency-based teaching, supervision and assessment. However, in many low- and middle-income and resource-constrained settings, faculty-to-student ratios substantially exceed ideal benchmarks, with ratios reported to reach as high as 1:45 [ 12 ]. Such staffing constraints not only affect the quality of teaching but also limit the capacity of institutions to adopt and sustain technology-enhanced approaches that require time, preparation, and ongoing educator engagement. Digital education technologies, including learning management systems (LMS), e-learning platforms, synchronous and asynchronous delivery formats, and simulation-based tools, have emerged as potential strategies to complement overstretched teaching systems and expand access to learning resources [ 13 , 14 ]. However, their successful implementation in resource-constrained settings depends on institutional readiness, educator capacity, and enabling infrastructure factors that remain underexamined within Nigerian midwifery training institutions. Across Africa, digital tools are increasingly being used in nursing and midwifery education, with initiatives reported in countries such as Ghana, Uganda, Rwanda, Malawi, Nigeria, and South Africa [ 17 – 19 ]. Evidence from Nigeria indicates that educators recognise the benefits of digital learning for flexibility and engagement; however, inadequate training, technical challenges, and weak institutional support continue to limit effective and sustained implementation [ 20 ]. In midwifery education specifically, available studies largely emerging during the COVID-19 pandemic highlight increased uptake but persistent structural barriers, including poor infrastructure, high connectivity costs, and limited digital literacy [ 9 , 21 , 22 ]. While digital technologies in midwifery education are well established in high-income settings [ 11 , 23 ], digital transformation in resource-constrained settings cannot be assumed to follow the same trajectory. Much of the literature on educational technology adoption focuses on individual-level determinants, such as perceived usefulness, perceived ease of use, and behavioural intention. Frameworks such as the Technology Acceptance Model (TAM) have been widely applied to explain adoption patterns in higher education settings [ 24 ]. However, these models typically presuppose the existence of stable infrastructural enabling conditions, including reliable electricity, connectivity, and institutional digital governance. In many LMIC training environments, these foundational conditions are uneven or fragile. In Nigeria specifically, existing research has focused largely on nursing education, with limited empirical evidence examining digital integration within midwifery training institutions [ 17 , 25 , 26 ]. Given the distinct regulatory structures, curriculum requirements, and clinical training demands of midwifery education, context-specific evidence on institutional readiness, teaching practices, and stakeholder experiences within midwifery schools is required. This study addresses these gaps through three objectives: (1) to explore the perceptions and experiences of midwifery educators, preceptors, and students regarding the integration and use of digital technology in midwifery education in Nigeria; (2) to assess institutional readiness for digital teaching and identify key enablers and barriers influencing the integration of digital tools in midwifery curricula and teaching practices; and (3) to examine perceived educational value and limitations of digital learning approaches in relation to conventional teaching methods in midwifery education. This study is part of a broader evaluation of maternal and newborn health innovations implemented under the Maternal and Neonatal Mortality Reduction Innovation and Initiatives (MAMII), led by the Nigerian government with support from the Gates Foundation. Consistent with the State of the World’s Midwifery 2021 report, sustained reductions in maternal mortality require strategic investments in high-quality, competency-based midwifery education [ 27 ]. Integrating digital and innovative learning approaches into pre-service training is increasingly recognised as essential for building a skilled and responsive midwifery workforce. Therefore, this study shifts the analytical focus from individual acceptance to institutional capacity. We conceptualise digital teaching readiness as a function of structural enabling conditions, including energy reliability, connectivity, access to functional digital infrastructure, and observable integration of ICT into classroom practice, as well as stakeholder perceptions. To operationalise this construct, we developed a Digital Teaching Readiness Index (DTRI) tailored for midwifery training institutions in resource-constrained environments. The DTRI provides a structured benchmarking framework that distinguishes infrastructural readiness from behavioural acceptance. By generating empirical evidence from educators, preceptors, and students, this study aims to inform Nigeria’s national strategies for digital integration in midwifery education. Methods Study design A convergent parallel mixed-methods design was employed to assess digital readiness and the use of digital technologies in Nigeria’s pre-service midwifery education. Quantitative and qualitative data were collected concurrently, analysed separately, and integrated during interpretation to generate meta-inferences regarding institutional readiness, educator and student experiences, and structural facilitators and barriers to digital integration. A narrative joint display approach was used to align institutional Digital Teaching Readiness Index (DTRI) scores with qualitative themes on infrastructure constraints, staffing pressures, and the perceived usefulness and feasibility of digital tools. Study setting and participants The study was conducted in 19 accredited midwifery training institutions across five geopolitical zones in Nigeria. Institutions included both federal and state-owned schools that delivered diploma- and degree-level midwifery education. Institutions were purposively selected in collaboration with the national regulatory body to ensure diversity in ownership, geographic location, and program type. Participants comprised midwifery educators involved in pre-service teaching, clinical preceptors supporting student learning in practice settings, final-year midwifery students, and institutional leaders or stakeholders involved in programme oversight, including heads of schools and programme coordinators. The eligibility criteria included current involvement in the teaching, learning, or management of pre-service midwifery programmes. Quantitative data collection Institutional digital readiness assessment A Digital Teaching Readiness Index (DTRI; range 0-100) was developed as a pragmatic benchmarking tool to summarise and compare the institutional capacity for digital teaching across midwifery schools included in this study. The index was designed to capture the foundational infrastructure and observable teaching practices required for digital education in resource-constrained settings, rather than to function as a psychometrically validated scale. The DTRI comprised five indicators drawn from the institutional checklist and structured teaching observations: (1) student Internet access (25 points), (2) availability of functional computer laboratories or library computers (25), (3) projector availability for teaching (15), (4) learning management system (LMS) use (15), and (5) observed ICT use during teaching sessions (20). Weights were assigned a priori to reflect the relative importance of core infrastructural prerequisites (Internet access and computer availability) compared with enabling technologies and enacted teaching practice. The research team agreed on the weighting decisions based on feasibility considerations and contextual relevance to low-resource training environments. The component scores were summed to generate an overall institutional score (0-100), with higher scores indicating greater readiness for digital teaching. Although the DTRI was calculated additively, student Internet access and functional computer availability were conceptualised as foundational infrastructural prerequisites for meaningful digital integration. The DTRI was used for descriptive and comparative analyses only and should be interpreted as an indicative institutional benchmark rather than a validated measure of digital capacity. [Insert Table 1 here] Table 1 Components and Scoring Structure of the Digital Teaching Readiness Index (DTRI) Component Indicator Definition Scoring Rule Weight (Points) Rationale Student Internet Access Institutional provision of internet access for students to access digital/online learning resources 0 = No institutional internet access; 25 = Internet access available to students 25 Foundational requirement for digital teaching and access to online resources Functional Computer Laboratory / Library Computers Availability of functional computers accessible to students 0 = None; 25 = Functional computers available 25 Enables equitable student access to digital learning materials Projector Availability for Teaching Availability and reported use of projectors in teaching curriculum 0 = Not available; 15 = Available 15 Facilitates multimedia-enhanced classroom teaching Learning Management System (LMS) Use Use of structured LMS (e.g., Moodle) as part of teaching delivery 0 = No LMS; 15 = LMS integrated in curriculum 15 Indicates structured digital pedagogy beyond informal platforms Observed ICT Use in Teaching Sessions ICT use observed during structured teaching observations 0 = No ICT observed; 20 = ICT observed in at least one session 20 Reflects actual classroom implementation rather than institutional reporting Total Possible Score: 100 Interpretation categories used in analysis: 60 = High readiness Teaching observations Structured non-participant observations were conducted across 37 teaching sessions delivered by the educators in the participating institutions. Sessions were purposively selected to capture variations in class size, course type, and institutional context. Observations were undertaken using a standardised checklist completed by trained researchers, with field notes recorded immediately after each session. The observation tool assessed the use of digital tools during teaching, pedagogical approaches, student engagement, and contextual constraints (e.g. power supply and connectivity). ICT use was defined as the use of any digital or electronic teaching tool during the observed session, including projectors, presentation slides, multimedia content, or online platforms. Observations were limited to the sampled sessions and may not reflect the routine teaching practices across the institution. Qualitative data collection Semi-structured in-depth interviews (IDIs) were conducted with educators and preceptors and focus group discussions (FGDs) were conducted with students. The interview and discussion guides were developed specifically for this study by the research team, informed by the study objectives and relevant literature on digital learning and midwifery education, and were tailored to each participant group (see Supplementary File 1). The topic guides explored experiences with digital teaching and learning, perceived facilitators and barriers to digital integration, institutional and regulatory influences, and equity implications of digital education. Interviews and discussions were audio-recorded, transcribed verbatim, and anonymised prior to analysis. Conceptual Framework and Analytical Approach The analysis was informed by concepts from the Technology Acceptance Model (TAM), particularly perceived usefulness and perceived ease of use, to help interpret the stakeholders’ perceptions of digital integration [ 24 ]. A digital readiness lens was also applied to examine enabling conditions, including infrastructure, educator capacity, and organisational support. In qualitative analysis, the coding framework incorporated sensitising constructs derived from the TAM and digital readiness domains, alongside inductive codes emerging from the data. Quantitatively, the DTRI served as a pragmatic operational indicator of the enabling conditions for digital teaching in institutions. Mixed-methods integration compared readiness scores and observed teaching practice with participant accounts to explore areas of convergence, divergence and explanatory patterns. Data analysis Quantitative Analysis Descriptive statistics were used to summarise the institutional characteristics, educator and student access to digital tools, and patterns of digital technology use. Given the limited number of institutions (N = 19), inferential modelling was not pursued. Associations between student-educator ratios and DTRI scores were explored using Spearman’s rank correlation to assess monotonic relationships between staffing levels and digital readiness. Analyses were conducted for exploratory purposes and were interpreted cautiously. Qualitative Analysis Qualitative data were analysed thematically using an inductive-deductive approach. An initial coding framework was informed by sensitising concepts derived from TAM (perceived usefulness and perceived ease of use) and the digital readiness domains. These constructs guided early coding but did not constrain the analysis, allowing themes to emerge inductively from the data. The codes were iteratively refined throughout the analysis. Coding was conducted independently by two researchers, and discrepancies were resolved through discussion to enhance analytical rigor. Integration of Quantitative and Qualitative Findings Integration occurred at the interpretation stage using a narrative joint display approach to compare institutional DTRI scores and observed teaching practices with the qualitative accounts of educators and students. The findings were examined for convergence, complementarity, and divergence, enabling the development of explanatory insights into institutional readiness and implementation dynamics. Ethical considerations Ethical approval for this study was obtained from the National Health Research Ethics Committee of Nigeria (NHREC) and relevant institutional review boards of participating institutions. All participants provided informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Results Institutional Profile of Midwifery Schools The midwifery schools varied widely in size, program types, staffing capacity, and digital readiness. Table 2 summarises the institutional characteristics of the 19 participating midwifery schools, while detailed institutional profiles are presented in Supplementary Table 1. The average number of final-year midwifery students was 78.6 (SD = 50.9), with state-funded schools having a higher mean (85.7) than federal institutions (58.6). Similarly, the mean number of newly admitted students in the 2023/24 session was higher in state-funded schools (140.3; SD = 73.1) than in federal schools (80.8; SD = 47.9). Most institutions (94.7%) offered the three-year basic midwifery program, while 57.9% also ran the two-year community midwifery program, and 31.6% offered the 18-month post-basic program. In terms of governance, 14 (73.7%) were state-funded and five (26.3%) were federally funded. The educator workforce was predominantly female across institutions, with a small number of male educators. On average, each institution had 10.5 educators (SD = 5.1), with higher mean staffing levels in federal institutions (13.0) than in state-funded institutions (9.6). The mean number of female educators per institution was 8.9, while the mean number of male educators was 0.5. In terms of qualifications, nearly all institutions had at least one educator with a nursing or midwifery degree. A total of 38 midwifery educators held master’s degrees, with 13 institutions (68%) having at least one master’s degree holder. Additionally, 132 educators across 16 institutions (84%) had additional teaching qualifications beyond their clinical training. Student-educator ratios varied considerably, ranging from 8:1 to 282:1. Other institutions, have ratios as high as 114:1 and others 64:1, also reported high admission ratios. Table 2 summarises the institutional characteristics of the 19 participating midwifery schools. [Insert Table 2 here] Table 2 Summary of institutional characteristics of participating midwifery schools (N = 19) Characteristic Category Number of institutions % Final-year student enrolment < 50 students 4 21.1 50–79 students 4 21.1 ≥ 80 students 11 57.9 Student admissions (2023/24) 10 educators 5 26.3 Student–educator ratio ≤ 30 6 31.6 31–60 7 36.8 > 60 6 31.6 Educators with additional teaching qualification ≥ 1 present 16 84.2 None 3 15.8 Educators with nursing/midwifery degree ≥ 1 present 18 94.7 None 1 5.3 Educators with master’s degree ≥ 1 present 13 68.4 None 6 31.6 Institutional funding State-funded 14 73.7 Federal-funded 5 26.3 Programme type offered* Basic midwifery (3 years) 18 94.7 Community midwifery (2 years) 11 57.9 Post-basic midwifery (18 months) 6 31.6 *Institutions may offer more than one program type. Qualitative findings provided further insights into how staffing patterns affected day-to-day teaching practices. Theme 1: Inadequate Staffing and High Student Load Qualitative findings indicated that large class sizes and limited teaching staff were widely perceived as operational challenges in the participating institutions. Educators described situations where a single lecturer was responsible for over 100 students. “ There is a gross lack of manpower… you find out in a class you have more than 100 students and it is only one lecturer that will be responsible, so for you to teach 100 students and then have effective teaching in that class for everybody to understand is very difficult…” – Educator 8 Another participant highlighted how the rapid expansion in student numbers has outpaced faculty recruitment as seen in the data extract below “…with the increase in the number of students, I feel that the number of lecturers to the student ratio is not sufficient, that's one of the greatest gaps we experience…” Educator 1 Availability and Use of Digital Tools Digital learning infrastructure was limited across the 19 participating midwifery institutions, with variations by funding type (Table 3 ). Detailed distributions of digital teaching infrastructure and online platforms across institutions are presented in Supplementary Table 2. Only five institutions (26.3%) provided internet access for students. Functional computers in libraries or computer laboratories were available in eight institutions (42.1%). Only one institution (5.3%) reported the structured use of a learning management system (LMS), such as Moodle, as part of its teaching curriculum. Similarly, only one federal institution (20% of federal schools; 5.3% overall) reported the routine use of video projectors in teaching sessions, and none of the state-funded institutions reported projector use. The informal use of online platforms was reported in a small number of institutions. Two institutions (10.5%) indicated the use of YouTube for teaching, and similar proportions reported the use of Google or TikTok for educational purposes. These infrastructural indicators informed the construction of the Digital Teaching Readiness Index (DTRI), which was subsequently used to assess institutional readiness for digital teaching across participating schools. [Insert Table 3 here] Table 3 Digital learning infrastructure and reported use by institutional funding type (N = 19) Digital Learning Infrastructure State-Funded Federal- Funded Total Count % Count % Count % Number of institutions 14 5 19 Video projectors used in teaching curriculum 0 (0) 1 (20) 1 (5) Internet access for students to access digital/online resources (for example, Moodle) 3 (21) 2 (40) 5 (26) Library/computer lab with functional computers for students 6 (43) 2 (40) 8 (42) Learning management system (Moodle) used in teaching curriculum 1 (7) 0 (0) 1 (5) YouTube used in teaching curriculum 1 (7) 1 (20) 2 (11) Google or web-based search used in teaching curriculum 1 (7) 1 (20) 2 (11) TikTok used in teaching curriculum 1 (7) 1 (20) 2 (11) Theme 2: Emerging Use of Informal Digital Platforms for Teaching Qualitative findings illustrated how educators and students adapted to limited formal infrastructure by relying on informal digital platforms to support the teaching and learning process. Educators described using WhatsApp groups to share lecture notes, practice questions, and supplementary teaching materials. “ We created a WhatsApp group where we post questions, lecture notes and some teaching aids that will help them to understand what we’ve taught… Now we are preparing for exams, sometimes we will post exam (practice) questions on that group.” - Educator 2 Some institutions reported using freely available online videos during training sessions, particularly for demonstrating clinical procedures. “ We had training for life-saving skills for [final year students]. It was YouTube videos we showed on how bleeding can be quantified, counselling and then monitoring of vital signs…” - Educator 7 Students similarly described using YouTube to reinforce complex theoretical concepts. “ We have used YouTube to watch many videos… I have learnt much on YouTube more than I've learnt even in class, especially that mechanism of labour, the complicated aspect.” - P4, FGD 1 One federal institution described a more structured deployment of Moodle for asynchronous content delivery. “…they put a server [Moodle] in our ICT centre, created a file for each staff and student. When you prepare your notes, you can upload the content… and the students at their own convenience go through what you have uploaded in the server.” - Educator 5 Use of Teaching Aids and Digital Tools in Observed Teaching Sessions A total of 37 teaching sessions were observed across the 19 participating institutions, comprising 26 sessions in state-funded schools and 11 sessions in federally funded institutions (Table 4 ). Detailed institutional distributions of teaching observations and instructional resources are provided in Supplementary Table 3. Teaching aids were not used in 17 sessions (46%), with non-use more frequently observed in federal institutions (64%) than in state-funded institutions (38%). Among sessions in which teaching aids were used, anatomical models were the most common resource, applied in 10 sessions (27%) across both institution types. Visual aids such as posters or illustrations were used in five sessions (14%), while flip charts were used in only one session (3%), which occurred in a state-funded institution. Information and communication technology (ICT) was observed in 6 of the 37 sessions (16%), all of which occurred in state-funded institutions. None of the observed sessions in federally funded institutions utilised digital teaching tools during the sampled sessions. At the institutional level, at least one session featuring ICT use was observed in six of the 19 institutions (31.6%). Institutional reports of projectors or other digital resources did not consistently correspond with observed classroom use during the sampled sessions. Regarding delivery quality indicators, 29 sessions (81%) featured legible written or projected teaching materials (whiteboards, overheads, or slides), with slightly higher rates in state institutions (84%) than federal institutions (73%). Competent handling of teaching materials was observed in 24 sessions (89%), including all sessions in federal institutions (100%) and 84% of sessions in state institutions. [Insert Table 4 here] Table 4 Summary of teaching observations: use of instructional aids and digital tools by institutional funding type Number of sessions observed State-Funded Federal-Funded Total 26 11 37 Teaching aids used: None 10 (38%) 7 (64%) 17(46%) Visual aids 4 (15%) 1 (9%) 5 (14%) Flip charts 1 (4%) 0 (0%) 1 (3%) Models 7 (27%) 3 (27%) 10 (27%) Information and communication technology (ICT) 6 (23%) 0 (0%) 6 (16%) Legibility of written or projected teaching materials 21 (84%) 8 (73%) 29 (81%) The resource materials were handled competently 16 (84%) 8 (100%) 24 (89%) Qualitative Findings: Contextualising Observed Patterns While the observational data quantified patterns of teaching aid and ICT use, the qualitative findings provided additional context regarding resource availability and access within institutions. Theme 4: Teaching Aids and Digital Tools Constrained by Outdated Resources and Limited Access. Educators described limited access to functional and up-to-date teaching resources. Several participants noted that existing laboratory equipment and instructional models were outdated. “ Our labs are becoming obsolete [outdated], the teaching aids are old, and they need to be changed. We still have the old model, the old care plan, everything is just not current…” - Educator 8 Participants also reported that access to shared resources, such as projectors, was limited. “ We have limited projectors which all the lecturers cannot easily have access to, so you find that mostly, the staff will just prefer to prepare their normal notes using their pen and paper.” – Educator 4 Challenges related to electricity supply were also described. “…if there is no light… you cannot deliver your lecture using digital equipment. And sometimes the generator is faulty or there is no fuel…” - Educator 8 These accounts describe infrastructural and access-related constraints, which were also reflected in the limited ICT use observed during teaching sessions. Overall distribution of Digital Teaching Readiness Index (DTRI) scores Using the Digital Teaching Readiness Index (DTRI) defined in the Methods section, institutional digital teaching capacity was summarised across the 19 participating midwifery schools. The DTRI scores ranged from 0 to 60 out of a possible 100 (Table 5 ). No institution met all five assessed readiness components. Overall, 11 institutions (57.9%) recorded DTRI scores below 20, indicating very low digital readiness. Six institutions (31.6%) scored between 40 and 60, representing moderate levels of readiness, while two institutions (10.5%) recorded scores between 20 and 39, suggesting emerging readiness for digital teaching. [Insert Table 5 here] Table 5 Institutional Digital Teaching Readiness Index (DTRI) scores across participating midwifery schools (N = 19) Institution Internet (25) Computer lab (25) Projector (15) LMS (15) Observed ICT use (20) Total DTRI (100) Institution 1 25 25 0 0 0 50 Institution 2 0 0 15 0 0 15 Institution 3 25 25 0 0 0 50 Institution 4 0 0 0 0 0 0 Institution 5 25 25 0 0 10 60 Institution 6 25 25 0 0 10 60 Institution 7 0 0 0 0 0 0 Institution 8 0 0 0 0 0 0 Institution 9 0 25 0 0 10 35 Institution 10 25 25 0 0 0 50 Institution 11 0 25 0 0 10 35 Institution 12 0 0 0 0 10 10 Institution 13 0 0 0 0 10 10 Institution 14 0 0 0 0 10 10 Institution 15 0 0 0 0 10 10 Institution 16 0 0 0 0 0 0 Institution 17 0 25 0 15 0 40 Institution 18 0 0 0 0 0 0 Institution 19 0 0 0 0 0 0 Note: Institutions were anonymised for confidentiality Contribution of infrastructure and teaching practices to DTRI scores Institutions with student Internet access (n = 5) and functional computer laboratories (n = 8) consistently recorded higher DTRI scores than those lacking these components. In contrast, structured LMS use (n = 1), and routine projector use (n = 1) were rare, contributing little to the overall score variation. ICT use during the observed teaching sessions was recorded in six institutions (31.6%). Institutions where ICT was observed generally recorded higher DTRI scores; however, no institution demonstrated consistent ICT use across all the observed sessions. Institutional patterns in digital teaching readiness Marked variations were observed among the institutions. Two institutions achieved the highest DTRI scores (60/100). These scores corresponded with the presence of Internet access, functional computer laboratories, and observed ICT use during teaching sessions. In contrast, seven institutions recorded a DTRI score of zero, indicating the absence of any assessed digital readiness components. Institutions with moderate readiness scores typically demonstrated partial infrastructure availability, such as Internet access and computer laboratories, but lacked structured digital teaching platforms such as LMS or consistent classroom ICT integration. Digital readiness and student–educator ratios The median DTRI scores varied across the staffing categories. Institutions with student-educator ratios between 31 and 60 recorded the highest median DTRI (35; IQR 10–50), whereas institutions with ratios ≤ 30 had a median DTRI of 5 (IQR 0–25). Institutions with ratios > 60 demonstrated substantial variability (median 25; IQR, 0–55). These findings indicate that digital readiness varied across staffing categories and was not uniformly higher in institutions with lower student-educator ratios than expected. [Insert Table 6 here] Table 6 Digital Teaching Readiness by student–educator ratio category Student–educator ratio Number of institutions Median DTRI (IQR) ≤ 30 6 5 (0–25) 31–60 7 35 (10–50) > 60 6 25 (0–55) Mixed-Methods Integration: Convergence of Quantitative and Qualitative Findings To enhance the integration of findings, a narrative joint display was constructed to align the key quantitative indicators of digital readiness with the qualitative explanations provided by educators and students. This approach enabled a comparison of the measured institutional capacity (e.g. infrastructure, DTRI scores, and observed ICT use) with the participants’ accounts of contextual barriers and adaptive practices. [Insert Table 7 here] Table 7 Narrative Joint Display Linking Quantitative Indicators of Digital Readiness with Qualitative Explanatory Themes Quantitative Finding Supporting Qualitative Explanation Only 5 of 19 institutions (26%) provided student internet access Participants reported unreliable connectivity and high mobile data costs, limiting digital learning access. Students described difficulty in affording personal data bundles. ICT observed in only 6 of 37 teaching sessions (16%) Educators cited limited projectors, unstable electricity, generator fuel shortages, and nonfunctional equipment as barriers to classroom ICT integration. Only 1 institution (5%) used a formal LMS Most institutions relied on informal platforms such as WhatsApp and YouTube for content sharing and for exam preparation. 11 institutions (57.9%) scored < 20 on DTRI Qualitative data highlighted systemic infrastructure gaps, a lack of institutional ICT policy, and limited budget prioritisation for digital education. Student-educator ratios ranged from 8:1 to 282:1 Educators described severe staff shortages and overcrowded classrooms, limiting their capacity to implement interactive or digitally enhanced teaching approaches. Moderate DTRI scores clustered in institutions with partial infrastructure (internet and computer lab) Institutions with partial infrastructure (e.g. Internet access and computer laboratories) recorded higher DTRI scores. Qualitative accounts from these institutions describe the greater use of informal digital practices. Association Between Staffing Levels and Digital Teaching Readiness Given the limited number of institutions (N = 19), inferential modelling was not pursued. Descriptive comparisons and correlation analyses were used to explore patterns between staffing levels and digital teaching readiness. Spearman rank correlation analysis demonstrated a moderate negative association between student and educator ratios and DTRI scores (ρ ≈ −0.58), indicating that institutions with higher student loads per educator tended to record lower digital readiness scores. However, substantial variability was observed, including isolated institutions with moderate DTRI scores despite high student–educator ratios. Theme 5: Perceived usefulness of digital technology in Midwifery education Despite infrastructural and staffing constraints, educators and students consistently expressed positive perceptions regarding the value and potential of digital technologies in midwifery education. Participants described digital tools, particularly video-based content and messaging platforms, as facilitating clearer understanding and enabling learning beyond classroom sessions. Visual teaching aids are frequently associated with improved comprehension and engagement. “ Digital technology is a necessity because it makes the teaching easier and understanding better … I prefer using videos for them because it gives you a clearer view and better understanding .” - Preceptor 2 “This digital learning, when you upload it to the server [Moodle] or prepare PowerPoint and send to their WhatsApp… even if they didn’t get it in class, when they go through it they can ask you privately or next time in class.” - Educator 5 Participants described digital platforms such as Moodle and WhatsApp as supporting resource sharing, revision, and follow-up communication between educators and students. Theme 6: Challenges to use of digital Technology Participants described unreliable electricity, limited access to devices, high mobile data costs, and restricted access to computer laboratories as ongoing barriers to digital integration. Institutional constraints, such as generator fuel shortages, limited projector availability, and staffing pressures, were frequently cited as limiting routine classroom ICT use. Several respondents suggested potential institutional improvements, including the provision of solar inverters, improved access to computer laboratories, and enhanced device availability for students. “A lot of things that will make for this digital learning, we don’t have them like projectors, solar panel, laptops, internet connectivity that is strong …” - Educator 8 “ Sometimes you might not have data to go through videos… Some of our colleagues don't have smartphones or laptops.” - P.16 , Focus Group 2 The challenges were also systemic, including staff shortages, overcrowded classes, and inability to access computer labs during non-class periods. Both students and staff described inconsistent use of digital tools due to generator fuel shortages, poor network coverage, and low prioritisation by the institutional leadership. “ We do have access to the computer lab during exams and some lectures… we cannot access it during break period for individual learning.” - Student, FGD 3 “…sometimes you maybe ask the provost to help you and talk to the engineer to provide the generator… they will tell you that the generator is faulty or maybe there is no fuel.” – Educator 8 However some respondents recommended practical solutions, including institutional provision of solar inverters, improving access to labs, and supporting students with compatible devices. “ Maybe if the school can be able to have solar inverter… it will be a very welcome idea… at least the inverter will be there, so when you are back from class, you'll be able to charge your phone and look for information .” P.3, FGD 1 Discussion This study provides mixed-methods evidence on the state of digital teaching readiness across 19 pre-service midwifery training institutions in Nigeria. Overall, the findings indicate that institutional readiness for digital integration remains limited and uneven. While educators and students expressed strong perceived usefulness of digital technologies and demonstrated adaptive informal practices to support learning, most institutions lacked foundational infrastructural prerequisites for structured digital education. Limited internet access, inadequate computer facilities, unreliable electricity supply, and high student–educator ratios collectively constrained the routine integration of digital tools into teaching practice. These findings suggest that digital transformation in midwifery education in resource-constrained settings is shaped primarily by structural enabling conditions rather than by attitudinal resistance, highlighting a persistent readiness–adoption gap. Digital readiness and institutional constraints The Digital Teaching Readiness Index (DTRI) showed substantial variation across institutions, but most schools lacked the core prerequisites for structured digital education. Internet access for students and functional computer laboratories were absent in the majority of schools, formal learning management system use was rare, and observed ICT use occurred in a small minority of teaching sessions [ 2 , 5 , 9 ]. Qualitative findings aligned with these patterns, indicating that unreliable electricity, limited access to shared teaching equipment (e.g. projectors), and constrained institutional budgets shaped what was feasible during routine teaching practices. Together, the quantitative and qualitative findings suggest that digital integration in many institutions remains dependent on individual initiatives rather than being supported by durable systems, policies, and infrastructure [ 2 , 5 ]. The observed variability across institutions also indicates that “readiness” is not a single characteristic but reflects interacting determinants of funding arrangements, infrastructure reliability, access to shared equipment, and institutional prioritisation. In this context, improving readiness is likely to require coordinated, institution-level investments rather than expecting individual educators or students to compensate for structural deficits alone. Acceptance of digital technologies under constrained conditions Qualitative findings were interpreted through the lens of the Technology Acceptance Model (TAM), which posits that perceived usefulness and perceived ease of use shape behavioural intention and technology adoption. Although perceived usefulness was consistently high across stakeholder groups, contextual barriers weakened perceived ease of use and constrained actual implementation. This divergence between intention and enacted practice underscores the importance of facilitating conditions, factors not explicitly foregrounded in classical TAM models but increasingly recognised in extended adoption frameworks [ 9 ]. Bridging Acceptance and Institutional Capacity: A Readiness-Adoption Gap A key contribution of this study is the identification of a persistent readiness–adoption gap in the literature. While stakeholders demonstrated high perceived usefulness and strong willingness to engage with digital tools, institutional systems lacked the infrastructural and organisational conditions necessary to translate acceptance into sustained implementation. This finding extends prior work from nursing and health professions education in sub-Saharan Africa, which has documented positive attitudes toward digital learning but uneven integration due to infrastructural fragility and limited institutional support [ 2 , 5 , 9 ]. Our mixed-methods evidence suggests that digital transformation in midwifery education is less constrained by attitudinal resistance and more by structural enabling conditions, including reliable power, connectivity, shared equipment, basic IT infrastructure, technical support, and policy alignment. This reframes digital integration not primarily as a behaviour-change problem but as a systems-strengthening challenge within health workforce education. These findings suggest that digital readiness in health professions education should be conceptualised as a layered systems construct rather than a single dimension of technology adoption. In resource-constrained training environments, digital integration depends on the alignment of foundational infrastructure, institutional governance, and educator capacity, which together shape the conditions under which behavioural acceptance can translate into sustained practice. The readiness–adoption gap observed in this study therefore highlights the need for implementation frameworks that explicitly incorporate infrastructural reliability and organisational enabling conditions alongside behavioural determinants of technology use. Recognising this layered relationship may help guide more realistic digital education policies and investments in low- and middle-income country training institutions. Pedagogical practices and informal digital adaptation Educators and students reported increased reliance on informal platforms, particularly WhatsApp for coordination and content sharing, and YouTube for visual reinforcement of complex concepts. While these strategies helped sustain learning in settings with limited formal systems, they also suggest that digital learning is currently occurring in uneven and unstandardised ways in Nigeria. Where access to devices and connectivity is variable, informal platform use may amplify inequities, as students without smartphones, stable network coverage, or affordable data are less able to benefit from online learning. In addition, reliance on informal tools raises questions regarding the consistency, quality assurance, and institutional oversight of teaching materials and learning interactions. Implications for curriculum delivery and quality High student-educator ratios and large class sizes were frequently described as limiting effective teaching and learner engagement in the literature. In such contexts, digital tools when used were more often described as supporting content transmission (e.g., sharing notes, videos, or slides) than enabling interactive, skills-based, or student-centred pedagogy. Without parallel investment in educator development for digital pedagogy and instructional design, digitalisation may replicate existing didactic approaches, rather than improve learning processes. Strengthening readiness therefore requires attention not only to infrastructure but also to how digital tools are integrated into teaching practices and curriculum delivery. Digital readiness as a health workforce systems issue Digital transformation in midwifery education should be situated within broader health workforce-strengthening agendas. Investment in digital infrastructure for training institutions may have spillover benefits for continuing professional development, data reporting, and the integration of digital health tools within service delivery. However, digitalisation strategies that focus solely on the procurement of equipment without parallel investment in maintenance systems, energy reliability, educator capacity, and governance alignment risk limited sustainability. Therefore, a phased, systems-oriented approach may be more appropriate than rapid technology deployment in resource-constrained contexts. Contribution to Knowledge This study makes three interrelated contributions to the literature on digital health professions education in low- and middle-income countries. First, it operationalises a Digital Teaching Readiness Index (DTRI) tailored to midwifery training institutions in resource-constrained settings. Unlike generic digital maturity frameworks, the DTRI explicitly prioritises foundational infrastructural prerequisites–student internet access, functional computer facilities, energy reliability, and observable classroom ICT use–as enabling conditions for digital pedagogy. In doing so, the index provides a replicable benchmarking framework that distinguishes structural readiness from behavioural acceptance. Although designed as a pragmatic tool rather than a psychometrically validated scale, the DTRI offers a structured approach for institutional self-assessment and comparative analysis across similar training contexts. Second, the study advances conceptual refinement through the articulation of the readiness–adoption gap . By integrating institutional assessment, classroom observation, and stakeholder perceptions, the findings demonstrate that a high perceived usefulness of digital technologies does not necessarily translate into sustained implementation where infrastructural capacity is weak. This insight extends the conventional applications of the Technology Acceptance Model by foregrounding structural enabling conditions as the primary determinants of adoption in low-resource settings. In doing so, the study reframes digital integration in midwifery education from a behaviour-change problem to a system-strengthening challenge. Third, this study provides rare multi-institutional empirical evidence specific to midwifery education in Nigeria, a domain that has been comparatively under-examined relative to nursing education. By distinguishing attitudinal readiness from infrastructural readiness and demonstrating how structural conditions mediate digital adoption, the findings contribute to a nuanced understanding of digital transformation in pre-service health workforce training. This evidence supports policy discourse that situates digital education within broader institutional capacity and governance reform rather than isolated technological interventions. Collectively, these contributions extend the existing literature by integrating institutional capacity assessment with theoretical interpretation and mixed-methods explanatory analysis. This study strengthens the conceptual foundation for future implementation research and policy design aimed at advancing equitable, sustainable digital transformation in midwifery education systems. Strengths and limitations The strengths of this study include its convergent mixed-methods design, multi-institutional scope across five geopolitical zones, and integration of institutional assessment, teaching observations, and stakeholder perspectives. Limitations include the purposive selection of institutions, possible reporting bias in self-reported institutional practices, and the limited number of teaching observations per institution, which may not fully capture routine practice. The DTRI was designed as a pragmatic benchmarking tool rather than as a psychometrically validated scale, and the findings should be interpreted accordingly. Finally, this study assessed institutional enabling conditions and observed teaching practices but did not measure learning outcomes, clinical competence, or downstream maternal/newborn outcomes. Therefore, the findings should be interpreted as evidence of readiness, adoption conditions, and implementation constraints in midwifery training institutions, rather than the impact of digital education on health outcomes. Implications for education, policy, and research For pre-service midwifery education in Nigeria, the findings support the need for structured, institution-level strategies that move beyond the ad hoc adoption of digital tools. Priority actions include strengthening reliable power supply (including solar-backed options where feasible), expanding affordable connectivity for students, improving access to functional computer facilities, and providing shared classroom equipment that supports the consistent use of digital teaching aids. Regulatory and accreditation bodies should consider incorporating minimum standards for digital infrastructure and pedagogical support into institutional approval and monitoring processes while recognising contextual constraints. Future research should assess how targeted investments, such as improved connectivity, educator training in digital pedagogy, and structured learning management system deployment, affect teaching practice, learning processes, and equity. Longitudinal studies could further explore whether exposure to structured digital learning environments during training influences early career practices and ongoing professional development. Conclusion This study demonstrates that although educators and students in Nigerian pre-service midwifery programmes recognise the value and potential of digital technologies, institutional readiness to support sustained and equitable digital integration remains limited and inconsistent. Foundational gaps in infrastructure, governance, and organisational support constrain systematic implementation, resulting in reliance on informal, educator-driven approaches that may inadvertently reinforce existing inequalities in access to learning resources. The findings indicate that digital transformation in midwifery education is not primarily constrained by attitudinal resistance but by structural and systems-level barriers. Bridging the readiness–adoption gap will require coordinated investments in reliable electricity and connectivity, functional computer facilities, structured learning management systems, and faculty development in digital pedagogy. In parallel, regulatory and accreditation bodies may need to articulate minimum digital infrastructure and quality standards to ensure consistency and equity across institutions. By generating multi-institutional, mixed-methods evidence from 19 midwifery training institutions, this study contributes empirical insights to the limited body of literature on digital readiness in midwifery education in low- and middle-income settings. The Digital Teaching Readiness Index (DTRI) offers a pragmatic benchmarking tool that may support institutional self-assessment and policy planning in this regard. As a simple, context-sensitive benchmarking framework, the DTRI may also support regulators, ministries of health and education, and training institutions in identifying priority investments and monitoring progress toward equitable digital capacity in midwifery education. Addressing the identified infrastructural and pedagogical constraints is essential to ensure that digital technologies enhance, rather than merely replicate, traditional models of teaching and to support the development of a competent and resilient midwifery workforce. Abbreviations NMCN: Nursing and Midwifery Council of Nigeria, NHREC: National Health Research Ethics Committee of Nigeria, FGD: focus group discussion, IDI: in-depth interviews, ICM: International Confederation of Midwives, LSTM: Liverpool School of Tropical Medicine Declarations Ethics approval and consent to participate Ethical approval for the study was obtained from the Liverpool School of Tropical Medicine Research Ethics Committee, United Kingdom (Approval reference: 24-074) and the National Health Research Ethics Committee of Nigeria (Approval reference: NHREC/01/01/2007-10/02/2025). All participants provided informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analysed during the current study are not publicly available due to ethical and confidentiality considerations but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was funded by the Bill & Melinda Gates Foundation (Investment ID: INV-084839). The funder had no role in the study design, data collection, analysis, interpretation of data, or decision to publish the findings. Authors’ contributions HMA: Conceptualization; Methodology; Investigation; Project administration; Data curation; Writing – original draft; Writing – review & editing. HM: Conceptualization; Methodology; Supervision; Writing – review & editing. ANL: Conceptualization; Methodology; Formal analysis; Writing – review & editing. SW: Formal analysis; Writing – review & editing. IG: Interpretation of findings; Writing – review & editing. MAL: Interpretation of findings; Writing – review & editing. OE: Interpretation of findings; Writing – review & editing. FD: Methodology; Data collection tools development; Writing – review & editing. CM: Methodology; Data collection tools development; Writing – review & editing. ABB: Project administration; Investigation; Writing – review & editing. NA: Institutional oversight; Technical guidance; Writing – review & editing. YT: Institutional oversight; Technical guidance; Writing – review & editing. CAA: Conceptualization; Methodology; Supervision; Funding acquisition; Writing – review & editing. All authors read and approved the final manuscript. Acknowledgements The authors thank the participating midwifery institutions, educators, preceptors and students for sharing their experiences and views. The authors also acknowledge the support of the Gates Foundation and implementing partners under the MAMII project. References Melisa M, Susanti AI. 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Ryhtä I, Elonen I, Saaranen T, Sormunen M, Mikkonen K, Kääriäinen M, et al. Social and health care educators’ perceptions of competence in digital pedagogy: a qualitative descriptive study. Nurse Educ Today. 2020;92:104521. Mbombi MO, Bopape MA, Ravele T, Ntho TA, Muthelo L, Phukubye TA, et al. Applying an e-learning framework to explore learner nurses’ and nurse educators’ perceptions about technology platforms in nursing. PLoS One. 2025;20(3):e0312681. Harerimana A, Wicking K, Biedermann N, Yates K. Integrating nursing informatics into undergraduate nursing education in Africa: a scoping review. Int Nurs Rev. 2021;68(3):420–433. Achampong EK. Assessing the current curriculum of the nursing and midwifery informatics course at nursing and midwifery institutions in Ghana. J Med Educ Curric Dev. 2017;4:2382120517706890. Eddy IN, Nyengidiki T, Ani G, Asagba P, Eleke C. Digital technologies used in nursing education: a systematic review of educators’ perspectives. J Nurs Midwifery Allied Health Sci. 2025;3(1):8–12. Addae HY, Alhassan A, Issah S, Azupogo F. Online learning experiences among nursing and midwifery students during the COVID-19 outbreak in Ghana: a cross-sectional study. Heliyon. 2022;8(12):e12155. Nsemo A. Perception, experiences and challenges of online and virtual learning during COVID-19 pandemic among student midwives of the Garden City University College, Kenyase-Kumasi, Ghana. Middle East J Res Educ Soc Sci. 2022. Akalin A, D’haenens F, Vermeulen J, Tricas-Sauras S, Lanssens D. Using digital technologies and applications in midwifery practice in Belgium: a descriptive cross-sectional study. Midwifery. 2025;140:104218. Holden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159–172. Owoeye ID, Chipps JA, Daniels F. Nurse educators’ competence and use of digital education technology at selected nursing education institutions in Nigeria. Int J Afr Nurs Sci. 2025;23:100870. Ishaq MN, Walugembe F. Perception of teachers and students towards the use of e-learning management system in Gombe State College of Nursing, Nigeria. SSRN Electron J. 2022. https://doi.org/10.2139/ssrn.4183443. UNFPA, ICM, WHO. State of the world’s midwifery 2021: building a health workforce to meet the needs of women, newborns and adolescents everywhere [Internet]. New York: UNFPA; 2021 [cited 2026 Feb 11]. Available from: https://www.unfpa.org/sites/default/files/pub-pdf/21-038-UNFPA-SoWMy2021-Report-ENv4302.pdf Additional Declarations No competing interests reported. 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This shift has reshaped teaching practices in nursing and midwifery, where effective digital integration has become central to delivering scalable, competency-based education. Digital approaches can support the development of core midwifery competencies by enhancing access to learning resources, facilitating interactive teaching, and complementing clinical training [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Nurse and midwife educators are increasingly expected to demonstrate digital competence to enhance learning, support student engagement, and maintain pedagogical effectiveness [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDigital education uses web-based technologies to support flexible and interactive learning, either fully online or blended with face-to-face instruction [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore digital learning can enhance engagement, access, and clinical competence, particularly in resource-constrained settings [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Equipping midwifery students with digital competencies is increasingly viewed as essential for sustaining quality and innovation in pre-service training [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlobal midwifery education frameworks emphasise the importance of adequate educator capacity to support competency-based teaching, supervision and assessment. However, in many low- and middle-income and resource-constrained settings, faculty-to-student ratios substantially exceed ideal benchmarks, with ratios reported to reach as high as 1:45 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Such staffing constraints not only affect the quality of teaching but also limit the capacity of institutions to adopt and sustain technology-enhanced approaches that require time, preparation, and ongoing educator engagement.\u003c/p\u003e \u003cp\u003eDigital education technologies, including learning management systems (LMS), e-learning platforms, synchronous and asynchronous delivery formats, and simulation-based tools, have emerged as potential strategies to complement overstretched teaching systems and expand access to learning resources [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, their successful implementation in resource-constrained settings depends on institutional readiness, educator capacity, and enabling infrastructure factors that remain underexamined within Nigerian midwifery training institutions.\u003c/p\u003e \u003cp\u003eAcross Africa, digital tools are increasingly being used in nursing and midwifery education, with initiatives reported in countries such as Ghana, Uganda, Rwanda, Malawi, Nigeria, and South Africa [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Evidence from Nigeria indicates that educators recognise the benefits of digital learning for flexibility and engagement; however, inadequate training, technical challenges, and weak institutional support continue to limit effective and sustained implementation [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In midwifery education specifically, available studies largely emerging during the COVID-19 pandemic highlight increased uptake but persistent structural barriers, including poor infrastructure, high connectivity costs, and limited digital literacy [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While digital technologies in midwifery education are well established in high-income settings [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], digital transformation in resource-constrained settings cannot be assumed to follow the same trajectory.\u003c/p\u003e \u003cp\u003eMuch of the literature on educational technology adoption focuses on individual-level determinants, such as perceived usefulness, perceived ease of use, and behavioural intention. Frameworks such as the Technology Acceptance Model (TAM) have been widely applied to explain adoption patterns in higher education settings [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. However, these models typically presuppose the existence of stable infrastructural enabling conditions, including reliable electricity, connectivity, and institutional digital governance. In many LMIC training environments, these foundational conditions are uneven or fragile.\u003c/p\u003e \u003cp\u003eIn Nigeria specifically, existing research has focused largely on nursing education, with limited empirical evidence examining digital integration within midwifery training institutions [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Given the distinct regulatory structures, curriculum requirements, and clinical training demands of midwifery education, context-specific evidence on institutional readiness, teaching practices, and stakeholder experiences within midwifery schools is required.\u003c/p\u003e \u003cp\u003eThis study addresses these gaps through three objectives:\u003c/p\u003e \u003cp\u003e(1) to explore the perceptions and experiences of midwifery educators, preceptors, and students regarding the integration and use of digital technology in midwifery education in Nigeria;\u003c/p\u003e \u003cp\u003e(2) to assess institutional readiness for digital teaching and identify key enablers and barriers influencing the integration of digital tools in midwifery curricula and teaching practices; and\u003c/p\u003e \u003cp\u003e(3) to examine perceived educational value and limitations of digital learning approaches in relation to conventional teaching methods in midwifery education.\u003c/p\u003e \u003cp\u003eThis study is part of a broader evaluation of maternal and newborn health innovations implemented under the Maternal and Neonatal Mortality Reduction Innovation and Initiatives (MAMII), led by the Nigerian government with support from the Gates Foundation. Consistent with the \u003cem\u003eState of the World\u0026rsquo;s Midwifery 2021\u003c/em\u003e report, sustained reductions in maternal mortality require strategic investments in high-quality, competency-based midwifery education [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Integrating digital and innovative learning approaches into pre-service training is increasingly recognised as essential for building a skilled and responsive midwifery workforce.\u003c/p\u003e \u003cp\u003eTherefore, this study shifts the analytical focus from individual acceptance to institutional capacity. We conceptualise digital teaching readiness as a function of structural enabling conditions, including energy reliability, connectivity, access to functional digital infrastructure, and observable integration of ICT into classroom practice, as well as stakeholder perceptions. To operationalise this construct, we developed a Digital Teaching Readiness Index (DTRI) tailored for midwifery training institutions in resource-constrained environments. The DTRI provides a structured benchmarking framework that distinguishes infrastructural readiness from behavioural acceptance.\u003c/p\u003e \u003cp\u003eBy generating empirical evidence from educators, preceptors, and students, this study aims to inform Nigeria\u0026rsquo;s national strategies for digital integration in midwifery education.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy design\u003c/h2\u003e\n \u003cp\u003eA convergent parallel mixed-methods design was employed to assess digital readiness and the use of digital technologies in Nigeria\u0026rsquo;s pre-service midwifery education. Quantitative and qualitative data were collected concurrently, analysed separately, and integrated during interpretation to generate meta-inferences regarding institutional readiness, educator and student experiences, and structural facilitators and barriers to digital integration. A narrative joint display approach was used to align institutional Digital Teaching Readiness Index (DTRI) scores with qualitative themes on infrastructure constraints, staffing pressures, and the perceived usefulness and feasibility of digital tools.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eStudy setting and participants\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in 19 accredited midwifery training institutions across five geopolitical zones in Nigeria. Institutions included both federal and state-owned schools that delivered diploma- and degree-level midwifery education. Institutions were purposively selected in collaboration with the national regulatory body to ensure diversity in ownership, geographic location, and program type.\u003c/p\u003e\n\u003cp\u003eParticipants comprised midwifery educators involved in pre-service teaching, clinical preceptors supporting student learning in practice settings, final-year midwifery students, and institutional leaders or stakeholders involved in programme oversight, including heads of schools and programme coordinators.\u003c/p\u003e\n\u003cp\u003eThe eligibility criteria included current involvement in the teaching, learning, or management of pre-service midwifery programmes.\u003c/p\u003e\n\u003ch3\u003eQuantitative data collection\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eInstitutional digital readiness assessment\u003c/h2\u003e\n \u003cp\u003eA Digital Teaching Readiness Index (DTRI; range 0-100) was developed as a pragmatic benchmarking tool to summarise and compare the institutional capacity for digital teaching across midwifery schools included in this study. The index was designed to capture the foundational infrastructure and observable teaching practices required for digital education in resource-constrained settings, rather than to function as a psychometrically validated scale.\u003c/p\u003e\n \u003cp\u003eThe DTRI comprised five indicators drawn from the institutional checklist and structured teaching observations: (1) student Internet access (25 points), (2) availability of functional computer laboratories or library computers (25), (3) projector availability for teaching (15), (4) learning management system (LMS) use (15), and (5) observed ICT use during teaching sessions (20). Weights were assigned a priori to reflect the relative importance of core infrastructural prerequisites (Internet access and computer availability) compared with enabling technologies and enacted teaching practice. The research team agreed on the weighting decisions based on feasibility considerations and contextual relevance to low-resource training environments.\u003c/p\u003e\n \u003cp\u003eThe component scores were summed to generate an overall institutional score (0-100), with higher scores indicating greater readiness for digital teaching. Although the DTRI was calculated additively, student Internet access and functional computer availability were conceptualised as foundational infrastructural prerequisites for meaningful digital integration. The DTRI was used for descriptive and comparative analyses only and should be interpreted as an indicative institutional benchmark rather than a validated measure of digital capacity.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e[Insert\u003c/strong\u003e Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cstrong\u003ehere]\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComponents and Scoring Structure of the Digital Teaching Readiness Index (DTRI)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eComponent\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eIndicator Definition\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eScoring Rule\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eWeight (Points)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eRationale\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eStudent Internet Access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eInstitutional provision of internet access for students to access digital/online learning resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026thinsp;=\u0026thinsp;No institutional internet access; 25\u0026thinsp;=\u0026thinsp;Internet access available to students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eFoundational requirement for digital teaching and access to online resources\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eFunctional Computer Laboratory / Library Computers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAvailability of functional computers accessible to students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026thinsp;=\u0026thinsp;None; 25\u0026thinsp;=\u0026thinsp;Functional computers available\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eEnables equitable student access to digital learning materials\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eProjector Availability for Teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eAvailability and reported use of projectors in teaching curriculum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026thinsp;=\u0026thinsp;Not available; 15\u0026thinsp;=\u0026thinsp;Available\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eFacilitates multimedia-enhanced classroom teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLearning Management System (LMS) Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eUse of structured LMS (e.g., Moodle) as part of teaching delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026thinsp;=\u0026thinsp;No LMS; 15\u0026thinsp;=\u0026thinsp;LMS integrated in curriculum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eIndicates structured digital pedagogy beyond informal platforms\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eObserved ICT Use in Teaching Sessions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eICT use observed during structured teaching observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0\u0026thinsp;=\u0026thinsp;No ICT observed; 20\u0026thinsp;=\u0026thinsp;ICT observed in at least one session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eReflects actual classroom implementation rather than institutional reporting\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\n \u003cp\u003eTotal Possible Score: 100\u003c/p\u003e\n \u003cp\u003eInterpretation categories used in analysis: \u003cstrong\u003e\u0026lt;20\u0026thinsp;=\u0026thinsp;Very low readiness; 20\u0026ndash;39\u0026thinsp;=\u0026thinsp;Emerging readiness; 40\u0026ndash;60\u0026thinsp;=\u0026thinsp;Moderate readiness; \u0026gt;60\u0026thinsp;=\u0026thinsp;High readiness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003eTeaching observations\u003c/h3\u003e\n\u003cp\u003eStructured non-participant observations were conducted across 37 teaching sessions delivered by the educators in the participating institutions. Sessions were purposively selected to capture variations in class size, course type, and institutional context. Observations were undertaken using a standardised checklist completed by trained researchers, with field notes recorded immediately after each session.\u003c/p\u003e\n\u003cp\u003eThe observation tool assessed the use of digital tools during teaching, pedagogical approaches, student engagement, and contextual constraints (e.g. power supply and connectivity). ICT use was defined as the use of any digital or electronic teaching tool during the observed session, including projectors, presentation slides, multimedia content, or online platforms. Observations were limited to the sampled sessions and may not reflect the routine teaching practices across the institution.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eQualitative data collection\u003c/h2\u003e\n \u003cp\u003eSemi-structured in-depth interviews (IDIs) were conducted with educators and preceptors and focus group discussions (FGDs) were conducted with students. The interview and discussion guides were developed specifically for this study by the research team, informed by the study objectives and relevant literature on digital learning and midwifery education, and were tailored to each participant group (see Supplementary File 1). The topic guides explored experiences with digital teaching and learning, perceived facilitators and barriers to digital integration, institutional and regulatory influences, and equity implications of digital education. Interviews and discussions were audio-recorded, transcribed verbatim, and anonymised prior to analysis.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eConceptual Framework and Analytical Approach\u003c/h3\u003e\n\u003cp\u003eThe analysis was informed by concepts from the Technology Acceptance Model (TAM), particularly perceived usefulness and perceived ease of use, to help interpret the stakeholders\u0026rsquo; perceptions of digital integration [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A digital readiness lens was also applied to examine enabling conditions, including infrastructure, educator capacity, and organisational support.\u003c/p\u003e\n\u003cp\u003eIn qualitative analysis, the coding framework incorporated sensitising constructs derived from the TAM and digital readiness domains, alongside inductive codes emerging from the data. Quantitatively, the DTRI served as a pragmatic operational indicator of the enabling conditions for digital teaching in institutions. Mixed-methods integration compared readiness scores and observed teaching practice with participant accounts to explore areas of convergence, divergence and explanatory patterns.\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eData analysis\u003c/h2\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003eQuantitative Analysis\u003c/h2\u003e\n \u003cp\u003eDescriptive statistics were used to summarise the institutional characteristics, educator and student access to digital tools, and patterns of digital technology use.\u003c/p\u003e\n \u003cp\u003eGiven the limited number of institutions (N\u0026thinsp;=\u0026thinsp;19), inferential modelling was not pursued. Associations between student-educator ratios and DTRI scores were explored using Spearman\u0026rsquo;s rank correlation to assess monotonic relationships between staffing levels and digital readiness. Analyses were conducted for exploratory purposes and were interpreted cautiously.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eQualitative Analysis\u003c/h2\u003e\n \u003cp\u003eQualitative data were analysed thematically using an inductive-deductive approach. An initial coding framework was informed by sensitising concepts derived from TAM (perceived usefulness and perceived ease of use) and the digital readiness domains. These constructs guided early coding but did not constrain the analysis, allowing themes to emerge inductively from the data.\u003c/p\u003e\n \u003cp\u003eThe codes were iteratively refined throughout the analysis. Coding was conducted independently by two researchers, and discrepancies were resolved through discussion to enhance analytical rigor.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eIntegration of Quantitative and Qualitative Findings\u003c/h2\u003e\n \u003cp\u003eIntegration occurred at the interpretation stage using a narrative joint display approach to compare institutional DTRI scores and observed teaching practices with the qualitative accounts of educators and students. The findings were examined for convergence, complementarity, and divergence, enabling the development of explanatory insights into institutional readiness and implementation dynamics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eEthical considerations\u003c/h2\u003e\n \u003cp\u003eEthical approval for this study was obtained from the National Health Research Ethics Committee of Nigeria (NHREC) and relevant institutional review boards of participating institutions. All participants provided informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eInstitutional Profile of Midwifery Schools\u003c/h2\u003e \u003cp\u003eThe midwifery schools varied widely in size, program types, staffing capacity, and digital readiness. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarises the institutional characteristics of the 19 participating midwifery schools, while detailed institutional profiles are presented in Supplementary Table\u0026nbsp;1. The average number of final-year midwifery students was 78.6 (SD\u0026thinsp;=\u0026thinsp;50.9), with state-funded schools having a higher mean (85.7) than federal institutions (58.6). Similarly, the mean number of newly admitted students in the 2023/24 session was higher in state-funded schools (140.3; SD\u0026thinsp;=\u0026thinsp;73.1) than in federal schools (80.8; SD\u0026thinsp;=\u0026thinsp;47.9).\u003c/p\u003e \u003cp\u003eMost institutions (94.7%) offered the three-year basic midwifery program, while 57.9% also ran the two-year community midwifery program, and 31.6% offered the 18-month post-basic program. In terms of governance, 14 (73.7%) were state-funded and five (26.3%) were federally funded.\u003c/p\u003e \u003cp\u003eThe educator workforce was predominantly female across institutions, with a small number of male educators. On average, each institution had 10.5 educators (SD\u0026thinsp;=\u0026thinsp;5.1), with higher mean staffing levels in federal institutions (13.0) than in state-funded institutions (9.6). The mean number of female educators per institution was 8.9, while the mean number of male educators was 0.5.\u003c/p\u003e \u003cp\u003eIn terms of qualifications, nearly all institutions had at least one educator with a nursing or midwifery degree. A total of 38 midwifery educators held master\u0026rsquo;s degrees, with 13 institutions (68%) having at least one master\u0026rsquo;s degree holder. Additionally, 132 educators across 16 institutions (84%) had additional teaching qualifications beyond their clinical training.\u003c/p\u003e \u003cp\u003eStudent-educator ratios varied considerably, ranging from 8:1 to 282:1. Other institutions, have ratios as high as 114:1 and others 64:1, also reported high admission ratios. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarises the institutional characteristics of the 19 participating midwifery schools.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of institutional characteristics of participating midwifery schools (N\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber of institutions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFinal-year student enrolment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;79 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStudent admissions (2023/24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u0026ndash;99 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;100 students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of educators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;10 educators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10 educators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStudent\u0026ndash;educator ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducators with additional teaching qualification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1 present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEducators with nursing/midwifery degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1 present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEducators with master\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;1 present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInstitutional funding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eState-funded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFederal-funded\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eProgramme type offered*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasic midwifery (3 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommunity midwifery (2 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-basic midwifery (18 months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Institutions may offer more than one program type.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eQualitative findings provided further insights into how staffing patterns affected day-to-day teaching practices.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eTheme 1: Inadequate Staffing and High Student Load\u003c/h2\u003e \u003cp\u003eQualitative findings indicated that large class sizes and limited teaching staff were widely perceived as operational challenges in the participating institutions. Educators described situations where a single lecturer was responsible for over 100 students.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eThere is a gross lack of manpower\u0026hellip; you find out in a class you have more than 100 students and it is only one lecturer that will be responsible, so for you to teach 100 students and then have effective teaching in that class for everybody to understand is very difficult\u0026hellip;\u0026rdquo;\u003c/em\u003e \u0026ndash; \u003cb\u003eEducator 8\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAnother participant highlighted how the rapid expansion in student numbers has outpaced faculty recruitment as seen in the data extract below\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;\u0026hellip;with the increase in the number of students, I feel that the number of lecturers to the student ratio is not sufficient, that's one of the greatest gaps we experience\u0026hellip;\u0026rdquo;\u003c/em\u003e \u003cb\u003eEducator 1\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eAvailability and Use of Digital Tools\u003c/h2\u003e \u003cp\u003eDigital learning infrastructure was limited across the 19 participating midwifery institutions, with variations by funding type (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Detailed distributions of digital teaching infrastructure and online platforms across institutions are presented in Supplementary Table\u0026nbsp;2.\u003c/p\u003e \u003cp\u003eOnly five institutions (26.3%) provided internet access for students. Functional computers in libraries or computer laboratories were available in eight institutions (42.1%). Only one institution (5.3%) reported the structured use of a learning management system (LMS), such as Moodle, as part of its teaching curriculum. Similarly, only one federal institution (20% of federal schools; 5.3% overall) reported the routine use of video projectors in teaching sessions, and none of the state-funded institutions reported projector use.\u003c/p\u003e \u003cp\u003eThe informal use of online platforms was reported in a small number of institutions. Two institutions (10.5%) indicated the use of YouTube for teaching, and similar proportions reported the use of Google or TikTok for educational purposes.\u003c/p\u003e \u003cp\u003eThese infrastructural indicators informed the construction of the Digital Teaching Readiness Index (DTRI), which was subsequently used to assess institutional readiness for digital teaching across participating schools.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDigital learning infrastructure and reported use by institutional funding type (N\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDigital Learning Infrastructure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eState-Funded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eFederal- Funded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVideo projectors used in teaching curriculum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternet access for students to access digital/online resources (for example, Moodle)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLibrary/computer lab with functional computers for students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLearning management system (Moodle) used in teaching curriculum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYouTube used in teaching curriculum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoogle or web-based search used in teaching curriculum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTikTok used in teaching curriculum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTheme 2: Emerging Use of Informal Digital Platforms for Teaching\u003c/h2\u003e \u003cp\u003eQualitative findings illustrated how educators and students adapted to limited formal infrastructure by relying on informal digital platforms to support the teaching and learning process.\u003c/p\u003e \u003cp\u003eEducators described using WhatsApp groups to share lecture notes, practice questions, and supplementary teaching materials.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eWe created a WhatsApp group where we post questions, lecture notes and some teaching aids that will help them to understand what we\u0026rsquo;ve taught\u0026hellip; Now we are preparing for exams, sometimes we will post exam (practice) questions on that group.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eEducator 2\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSome institutions reported using freely available online videos during training sessions, particularly for demonstrating clinical procedures.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eWe had training for life-saving skills for [final year students]. It was YouTube videos we showed on how bleeding can be quantified, counselling and then monitoring of vital signs\u0026hellip;\u0026rdquo;\u003c/em\u003e - \u003cb\u003eEducator 7\u003c/b\u003e\u003c/p\u003e \u003cp\u003eStudents similarly described using YouTube to reinforce complex theoretical concepts.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eWe have used YouTube to watch many videos\u0026hellip; I have learnt much on YouTube more than I've learnt even in class, especially that mechanism of labour, the complicated aspect.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eP4, FGD 1\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOne federal institution described a more structured deployment of Moodle for asynchronous content delivery.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;\u0026hellip;they put a server [Moodle] in our ICT centre, created a file for each staff and student. When you prepare your notes, you can upload the content\u0026hellip; and the students at their own convenience go through what you have uploaded in the server.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eEducator 5\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eUse of Teaching Aids and Digital Tools in Observed Teaching Sessions\u003c/h2\u003e \u003cp\u003eA total of 37 teaching sessions were observed across the 19 participating institutions, comprising 26 sessions in state-funded schools and 11 sessions in federally funded institutions (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Detailed institutional distributions of teaching observations and instructional resources are provided in Supplementary Table\u0026nbsp;3.\u003c/p\u003e \u003cp\u003eTeaching aids were not used in 17 sessions (46%), with non-use more frequently observed in federal institutions (64%) than in state-funded institutions (38%). Among sessions in which teaching aids were used, anatomical models were the most common resource, applied in 10 sessions (27%) across both institution types. Visual aids such as posters or illustrations were used in five sessions (14%), while flip charts were used in only one session (3%), which occurred in a state-funded institution.\u003c/p\u003e \u003cp\u003eInformation and communication technology (ICT) was observed in 6 of the 37 sessions (16%), all of which occurred in state-funded institutions. None of the observed sessions in federally funded institutions utilised digital teaching tools during the sampled sessions. At the institutional level, at least one session featuring ICT use was observed in six of the 19 institutions (31.6%).\u003c/p\u003e \u003cp\u003eInstitutional reports of projectors or other digital resources did not consistently correspond with observed classroom use during the sampled sessions.\u003c/p\u003e \u003cp\u003e Regarding delivery quality indicators, 29 sessions (81%) featured legible written or projected teaching materials (whiteboards, overheads, or slides), with slightly higher rates in state institutions (84%) than federal institutions (73%). Competent handling of teaching materials was observed in 24 sessions (89%), including all sessions in federal institutions (100%) and 84% of sessions in state institutions.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of teaching observations: use of instructional aids and digital tools by institutional funding type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of sessions observed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eState-Funded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFederal-Funded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeaching aids used: None\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17(46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisual aids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (14%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlip charts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (27%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInformation and communication technology (ICT)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (16%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegibility of written or projected teaching materials\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (73%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (81%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe resource materials were handled competently\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (89%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eQualitative Findings: Contextualising Observed Patterns\u003c/h2\u003e \u003cp\u003eWhile the observational data quantified patterns of teaching aid and ICT use, the qualitative findings provided additional context regarding resource availability and access within institutions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTheme 4: Teaching Aids and Digital Tools Constrained by Outdated Resources and Limited Access.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eEducators described limited access to functional and up-to-date teaching resources. Several participants noted that existing laboratory equipment and instructional models were outdated.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eOur labs are becoming obsolete [outdated], the teaching aids are old, and they need to be changed. We still have the old model, the old care plan, everything is just not current\u0026hellip;\u0026rdquo;\u003c/em\u003e -\u003cb\u003eEducator 8\u003c/b\u003e\u003c/p\u003e \u003cp\u003eParticipants also reported that access to shared resources, such as projectors, was limited.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eWe have limited projectors which all the lecturers cannot easily have access to, so you find that mostly, the staff will just prefer to prepare their normal notes using their pen and paper.\u0026rdquo;\u003c/em\u003e \u0026ndash; \u003cb\u003eEducator 4\u003c/b\u003e\u003c/p\u003e \u003cp\u003eChallenges related to electricity supply were also described.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;\u0026hellip;if there is no light\u0026hellip; you cannot deliver your lecture using digital equipment. And sometimes the generator is faulty or there is no fuel\u0026hellip;\u0026rdquo;\u003c/em\u003e - \u003cb\u003eEducator 8\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThese accounts describe infrastructural and access-related constraints, which were also reflected in the limited ICT use observed during teaching sessions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eOverall distribution of Digital Teaching Readiness Index (DTRI) scores\u003c/h2\u003e \u003cp\u003e Using the Digital Teaching Readiness Index (DTRI) defined in the Methods section, institutional digital teaching capacity was summarised across the 19 participating midwifery schools. The DTRI scores ranged from 0 to 60 out of a possible 100 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). No institution met all five assessed readiness components.\u003c/p\u003e \u003cp\u003eOverall, 11 institutions (57.9%) recorded DTRI scores below 20, indicating very low digital readiness. Six institutions (31.6%) scored between 40 and 60, representing moderate levels of readiness, while two institutions (10.5%) recorded scores between 20 and 39, suggesting emerging readiness for digital teaching.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInstitutional Digital Teaching Readiness Index (DTRI) scores across participating midwifery schools (N\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternet (25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComputer lab (25)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProjector (15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLMS (15)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eObserved ICT use (20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal DTRI (100)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eNote: Institutions were anonymised for confidentiality\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eContribution of infrastructure and teaching practices to DTRI scores\u003c/h2\u003e \u003cp\u003eInstitutions with student Internet access (n\u0026thinsp;=\u0026thinsp;5) and functional computer laboratories (n\u0026thinsp;=\u0026thinsp;8) consistently recorded higher DTRI scores than those lacking these components. In contrast, structured LMS use (n\u0026thinsp;=\u0026thinsp;1), and routine projector use (n\u0026thinsp;=\u0026thinsp;1) were rare, contributing little to the overall score variation.\u003c/p\u003e \u003cp\u003eICT use during the observed teaching sessions was recorded in six institutions (31.6%). Institutions where ICT was observed generally recorded higher DTRI scores; however, no institution demonstrated consistent ICT use across all the observed sessions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eInstitutional patterns in digital teaching readiness\u003c/h2\u003e \u003cp\u003eMarked variations were observed among the institutions. Two institutions achieved the highest DTRI scores (60/100). These scores corresponded with the presence of Internet access, functional computer laboratories, and observed ICT use during teaching sessions. In contrast, seven institutions recorded a DTRI score of zero, indicating the absence of any assessed digital readiness components.\u003c/p\u003e \u003cp\u003eInstitutions with moderate readiness scores typically demonstrated partial infrastructure availability, such as Internet access and computer laboratories, but lacked structured digital teaching platforms such as LMS or consistent classroom ICT integration.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eDigital readiness and student\u0026ndash;educator ratios\u003c/h2\u003e \u003cp\u003eThe median DTRI scores varied across the staffing categories. Institutions with student-educator ratios between 31 and 60 recorded the highest median DTRI (35; IQR 10\u0026ndash;50), whereas institutions with ratios\u0026thinsp;\u0026le;\u0026thinsp;30 had a median DTRI of 5 (IQR 0\u0026ndash;25). Institutions with ratios\u0026thinsp;\u0026gt;\u0026thinsp;60 demonstrated substantial variability (median 25; IQR, 0\u0026ndash;55).\u003c/p\u003e \u003cp\u003eThese findings indicate that digital readiness varied across staffing categories and was not uniformly higher in institutions with lower student-educator ratios than expected.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDigital Teaching Readiness by student\u0026ndash;educator ratio category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent\u0026ndash;educator ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of institutions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian DTRI (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0\u0026ndash;25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (10\u0026ndash;50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (0\u0026ndash;55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eMixed-Methods Integration: Convergence of Quantitative and Qualitative Findings\u003c/h2\u003e \u003cp\u003eTo enhance the integration of findings, a narrative joint display was constructed to align the key quantitative indicators of digital readiness with the qualitative explanations provided by educators and students. This approach enabled a comparison of the measured institutional capacity (e.g. infrastructure, DTRI scores, and observed ICT use) with the participants\u0026rsquo; accounts of contextual barriers and adaptive practices.\u003c/p\u003e \u003cp\u003e \u003cb\u003e[Insert\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e \u003cb\u003ehere]\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNarrative Joint Display Linking Quantitative Indicators of Digital Readiness with Qualitative Explanatory Themes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantitative Finding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSupporting Qualitative Explanation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly 5 of 19 institutions (26%) provided student internet access\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants reported unreliable connectivity and high mobile data costs, limiting digital learning access. Students described difficulty in affording personal data bundles.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICT observed in only 6 of 37 teaching sessions (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducators cited limited projectors, unstable electricity, generator fuel shortages, and nonfunctional equipment as barriers to classroom ICT integration.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnly 1 institution (5%) used a formal LMS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMost institutions relied on informal platforms such as WhatsApp and YouTube for content sharing and for exam preparation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11 institutions (57.9%) scored\u0026thinsp;\u0026lt;\u0026thinsp;20 on DTRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQualitative data highlighted systemic infrastructure gaps, a lack of institutional ICT policy, and limited budget prioritisation for digital education.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudent-educator ratios ranged from 8:1 to 282:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducators described severe staff shortages and overcrowded classrooms, limiting their capacity to implement interactive or digitally enhanced teaching approaches.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate DTRI scores clustered in institutions with partial infrastructure (internet and computer lab)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstitutions with partial infrastructure (e.g. Internet access and computer laboratories) recorded higher DTRI scores. Qualitative accounts from these institutions describe the greater use of informal digital practices.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eAssociation Between Staffing Levels and Digital Teaching Readiness\u003c/h2\u003e \u003cp\u003eGiven the limited number of institutions (N\u0026thinsp;=\u0026thinsp;19), inferential modelling was not pursued. Descriptive comparisons and correlation analyses were used to explore patterns between staffing levels and digital teaching readiness.\u003c/p\u003e \u003cp\u003eSpearman rank correlation analysis demonstrated a moderate negative association between student and educator ratios and DTRI scores (ρ \u0026asymp; \u0026minus;0.58), indicating that institutions with higher student loads per educator tended to record lower digital readiness scores. However, substantial variability was observed, including isolated institutions with moderate DTRI scores despite high student\u0026ndash;educator ratios.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eTheme 5: Perceived usefulness of digital technology in Midwifery education\u003c/h2\u003e \u003cp\u003eDespite infrastructural and staffing constraints, educators and students consistently expressed positive perceptions regarding the value and potential of digital technologies in midwifery education. Participants described digital tools, particularly video-based content and messaging platforms, as facilitating clearer understanding and enabling learning beyond classroom sessions. Visual teaching aids are frequently associated with improved comprehension and engagement.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eDigital technology is a necessity because it makes the teaching easier and understanding better \u0026hellip; I prefer using videos for them because it gives you a clearer view and better understanding\u003c/em\u003e.\u0026rdquo; - \u003cb\u003ePreceptor 2\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;This digital learning, when you upload it to the server [Moodle] or prepare PowerPoint and send to their WhatsApp\u0026hellip; even if they didn\u0026rsquo;t get it in class, when they go through it they can ask you privately or next time in class.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eEducator 5\u003c/b\u003e\u003c/p\u003e \u003cp\u003eParticipants described digital platforms such as Moodle and WhatsApp as supporting resource sharing, revision, and follow-up communication between educators and students.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eTheme 6: Challenges to use of digital Technology\u003c/h2\u003e \u003cp\u003eParticipants described unreliable electricity, limited access to devices, high mobile data costs, and restricted access to computer laboratories as ongoing barriers to digital integration. Institutional constraints, such as generator fuel shortages, limited projector availability, and staffing pressures, were frequently cited as limiting routine classroom ICT use.\u003c/p\u003e \u003cp\u003eSeveral respondents suggested potential institutional improvements, including the provision of solar inverters, improved access to computer laboratories, and enhanced device availability for students.\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;A lot of things that will make for this digital learning, we don\u0026rsquo;t have them like projectors, solar panel, laptops, internet connectivity that is strong\u003c/em\u003e\u0026hellip;\u0026rdquo; -\u003cb\u003eEducator 8\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eSometimes you might not have data to go through videos\u0026hellip; Some of our colleagues don't have smartphones or laptops.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eP.16\u003c/b\u003e, \u003cb\u003eFocus Group 2\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe challenges were also systemic, including staff shortages, overcrowded classes, and inability to access computer labs during non-class periods. Both students and staff described inconsistent use of digital tools due to generator fuel shortages, poor network coverage, and low prioritisation by the institutional leadership.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eWe do have access to the computer lab during exams and some lectures\u0026hellip; we cannot access it during break period for individual learning.\u0026rdquo;\u003c/em\u003e -\u003cb\u003eStudent, FGD 3\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003e\u0026ldquo;\u0026hellip;sometimes you maybe ask the provost to help you and talk to the engineer to provide the generator\u0026hellip; they will tell you that the generator is faulty or maybe there is no fuel.\u0026rdquo;\u003c/em\u003e \u0026ndash;\u003cb\u003eEducator 8\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHowever some respondents recommended practical solutions, including institutional provision of solar inverters, improving access to labs, and supporting students with compatible devices.\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u003cem\u003eMaybe if the school can be able to have solar inverter\u0026hellip; it will be a very welcome idea\u0026hellip; at least the inverter will be there, so when you are back from class, you'll be able to charge your phone and look for information\u003c/em\u003e.\u0026rdquo; \u003cb\u003eP.3, FGD 1\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides mixed-methods evidence on the state of digital teaching readiness across 19 pre-service midwifery training institutions in Nigeria. Overall, the findings indicate that institutional readiness for digital integration remains limited and uneven. While educators and students expressed strong perceived usefulness of digital technologies and demonstrated adaptive informal practices to support learning, most institutions lacked foundational infrastructural prerequisites for structured digital education. Limited internet access, inadequate computer facilities, unreliable electricity supply, and high student\u0026ndash;educator ratios collectively constrained the routine integration of digital tools into teaching practice. These findings suggest that digital transformation in midwifery education in resource-constrained settings is shaped primarily by structural enabling conditions rather than by attitudinal resistance, highlighting a persistent readiness\u0026ndash;adoption gap.\u003c/p\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eDigital readiness and institutional constraints\u003c/h2\u003e \u003cp\u003eThe Digital Teaching Readiness Index (DTRI) showed substantial variation across institutions, but most schools lacked the core prerequisites for structured digital education. Internet access for students and functional computer laboratories were absent in the majority of schools, formal learning management system use was rare, and observed ICT use occurred in a small minority of teaching sessions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eQualitative findings aligned with these patterns, indicating that unreliable electricity, limited access to shared teaching equipment (e.g. projectors), and constrained institutional budgets shaped what was feasible during routine teaching practices. Together, the quantitative and qualitative findings suggest that digital integration in many institutions remains dependent on individual initiatives rather than being supported by durable systems, policies, and infrastructure [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe observed variability across institutions also indicates that \u0026ldquo;readiness\u0026rdquo; is not a single characteristic but reflects interacting determinants of funding arrangements, infrastructure reliability, access to shared equipment, and institutional prioritisation. In this context, improving readiness is likely to require coordinated, institution-level investments rather than expecting individual educators or students to compensate for structural deficits alone.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eAcceptance of digital technologies under constrained conditions\u003c/h2\u003e \u003cp\u003eQualitative findings were interpreted through the lens of the Technology Acceptance Model (TAM), which posits that perceived usefulness and perceived ease of use shape behavioural intention and technology adoption. Although perceived usefulness was consistently high across stakeholder groups, contextual barriers weakened perceived ease of use and constrained actual implementation. This divergence between intention and enacted practice underscores the importance of facilitating conditions, factors not explicitly foregrounded in classical TAM models but increasingly recognised in extended adoption frameworks [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec33\" class=\"Section3\"\u003e \u003ch2\u003eBridging Acceptance and Institutional Capacity: A Readiness-Adoption Gap\u003c/h2\u003e \u003cp\u003eA key contribution of this study is the identification of a persistent readiness\u0026ndash;adoption gap in the literature. While stakeholders demonstrated high perceived usefulness and strong willingness to engage with digital tools, institutional systems lacked the infrastructural and organisational conditions necessary to translate acceptance into sustained implementation. This finding extends prior work from nursing and health professions education in sub-Saharan Africa, which has documented positive attitudes toward digital learning but uneven integration due to infrastructural fragility and limited institutional support [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Our mixed-methods evidence suggests that digital transformation in midwifery education is less constrained by attitudinal resistance and more by structural enabling conditions, including reliable power, connectivity, shared equipment, basic IT infrastructure, technical support, and policy alignment. This reframes digital integration not primarily as a behaviour-change problem but as a systems-strengthening challenge within health workforce education.\u003c/p\u003e \u003cp\u003eThese findings suggest that digital readiness in health professions education should be conceptualised as a layered systems construct rather than a single dimension of technology adoption. In resource-constrained training environments, digital integration depends on the alignment of foundational infrastructure, institutional governance, and educator capacity, which together shape the conditions under which behavioural acceptance can translate into sustained practice. The readiness\u0026ndash;adoption gap observed in this study therefore highlights the need for implementation frameworks that explicitly incorporate infrastructural reliability and organisational enabling conditions alongside behavioural determinants of technology use. Recognising this layered relationship may help guide more realistic digital education policies and investments in low- and middle-income country training institutions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section3\"\u003e \u003ch2\u003ePedagogical practices and informal digital adaptation\u003c/h2\u003e \u003cp\u003eEducators and students reported increased reliance on informal platforms, particularly WhatsApp for coordination and content sharing, and YouTube for visual reinforcement of complex concepts. While these strategies helped sustain learning in settings with limited formal systems, they also suggest that digital learning is currently occurring in uneven and unstandardised ways in Nigeria. Where access to devices and connectivity is variable, informal platform use may amplify inequities, as students without smartphones, stable network coverage, or affordable data are less able to benefit from online learning. In addition, reliance on informal tools raises questions regarding the consistency, quality assurance, and institutional oversight of teaching materials and learning interactions.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e\n\u003ch3\u003eImplications for curriculum delivery and quality\u003c/h3\u003e\n\u003cp\u003eHigh student-educator ratios and large class sizes were frequently described as limiting effective teaching and learner engagement in the literature. In such contexts, digital tools when used were more often described as supporting content transmission (e.g., sharing notes, videos, or slides) than enabling interactive, skills-based, or student-centred pedagogy. Without parallel investment in educator development for digital pedagogy and instructional design, digitalisation may replicate existing didactic approaches, rather than improve learning processes. Strengthening readiness therefore requires attention not only to infrastructure but also to how digital tools are integrated into teaching practices and curriculum delivery.\u003c/p\u003e\n\u003ch3\u003eDigital readiness as a health workforce systems issue\u003c/h3\u003e\n\u003cp\u003eDigital transformation in midwifery education should be situated within broader health workforce-strengthening agendas. Investment in digital infrastructure for training institutions may have spillover benefits for continuing professional development, data reporting, and the integration of digital health tools within service delivery. However, digitalisation strategies that focus solely on the procurement of equipment without parallel investment in maintenance systems, energy reliability, educator capacity, and governance alignment risk limited sustainability. Therefore, a phased, systems-oriented approach may be more appropriate than rapid technology deployment in resource-constrained contexts.\u003c/p\u003e \u003cdiv id=\"Sec37\" class=\"Section2\"\u003e \u003ch2\u003eContribution to Knowledge\u003c/h2\u003e \u003cp\u003eThis study makes three interrelated contributions to the literature on digital health professions education in low- and middle-income countries.\u003c/p\u003e \u003cp\u003eFirst, it operationalises a \u003cb\u003eDigital Teaching Readiness Index (DTRI)\u003c/b\u003e tailored to midwifery training institutions in resource-constrained settings. Unlike generic digital maturity frameworks, the DTRI explicitly prioritises foundational infrastructural prerequisites\u0026ndash;student internet access, functional computer facilities, energy reliability, and observable classroom ICT use\u0026ndash;as enabling conditions for digital pedagogy. In doing so, the index provides a replicable benchmarking framework that distinguishes structural readiness from behavioural acceptance. Although designed as a pragmatic tool rather than a psychometrically validated scale, the DTRI offers a structured approach for institutional self-assessment and comparative analysis across similar training contexts.\u003c/p\u003e \u003cp\u003eSecond, the study advances conceptual refinement through the articulation of the \u003cb\u003ereadiness\u0026ndash;adoption gap\u003c/b\u003e. By integrating institutional assessment, classroom observation, and stakeholder perceptions, the findings demonstrate that a high perceived usefulness of digital technologies does not necessarily translate into sustained implementation where infrastructural capacity is weak. This insight extends the conventional applications of the Technology Acceptance Model by foregrounding structural enabling conditions as the primary determinants of adoption in low-resource settings. In doing so, the study reframes digital integration in midwifery education from a behaviour-change problem to a system-strengthening challenge.\u003c/p\u003e \u003cp\u003eThird, this study provides rare multi-institutional empirical evidence specific to midwifery education in Nigeria, a domain that has been comparatively under-examined relative to nursing education. By distinguishing attitudinal readiness from infrastructural readiness and demonstrating how structural conditions mediate digital adoption, the findings contribute to a nuanced understanding of digital transformation in pre-service health workforce training. This evidence supports policy discourse that situates digital education within broader institutional capacity and governance reform rather than isolated technological interventions.\u003c/p\u003e \u003cp\u003eCollectively, these contributions extend the existing literature by integrating institutional capacity assessment with theoretical interpretation and mixed-methods explanatory analysis. This study strengthens the conceptual foundation for future implementation research and policy design aimed at advancing equitable, sustainable digital transformation in midwifery education systems.\u003c/p\u003e \u003cdiv id=\"Sec38\" class=\"Section3\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThe strengths of this study include its convergent mixed-methods design, multi-institutional scope across five geopolitical zones, and integration of institutional assessment, teaching observations, and stakeholder perspectives. Limitations include the purposive selection of institutions, possible reporting bias in self-reported institutional practices, and the limited number of teaching observations per institution, which may not fully capture routine practice. The DTRI was designed as a pragmatic benchmarking tool rather than as a psychometrically validated scale, and the findings should be interpreted accordingly. Finally, this study assessed institutional enabling conditions and observed teaching practices but did not measure learning outcomes, clinical competence, or downstream maternal/newborn outcomes. Therefore, the findings should be interpreted as evidence of readiness, adoption conditions, and implementation constraints in midwifery training institutions, rather than the impact of digital education on health outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003eImplications for education, policy, and research\u003c/h2\u003e \u003cp\u003eFor pre-service midwifery education in Nigeria, the findings support the need for structured, institution-level strategies that move beyond the ad hoc adoption of digital tools. Priority actions include strengthening reliable power supply (including solar-backed options where feasible), expanding affordable connectivity for students, improving access to functional computer facilities, and providing shared classroom equipment that supports the consistent use of digital teaching aids. Regulatory and accreditation bodies should consider incorporating minimum standards for digital infrastructure and pedagogical support into institutional approval and monitoring processes while recognising contextual constraints.\u003c/p\u003e \u003cp\u003eFuture research should assess how targeted investments, such as improved connectivity, educator training in digital pedagogy, and structured learning management system deployment, affect teaching practice, learning processes, and equity. Longitudinal studies could further explore whether exposure to structured digital learning environments during training influences early career practices and ongoing professional development.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that although educators and students in Nigerian pre-service midwifery programmes recognise the value and potential of digital technologies, institutional readiness to support sustained and equitable digital integration remains limited and inconsistent. Foundational gaps in infrastructure, governance, and organisational support constrain systematic implementation, resulting in reliance on informal, educator-driven approaches that may inadvertently reinforce existing inequalities in access to learning resources.\u003c/p\u003e \u003cp\u003eThe findings indicate that digital transformation in midwifery education is not primarily constrained by attitudinal resistance but by structural and systems-level barriers. Bridging the readiness\u0026ndash;adoption gap will require coordinated investments in reliable electricity and connectivity, functional computer facilities, structured learning management systems, and faculty development in digital pedagogy. In parallel, regulatory and accreditation bodies may need to articulate minimum digital infrastructure and quality standards to ensure consistency and equity across institutions.\u003c/p\u003e \u003cp\u003eBy generating multi-institutional, mixed-methods evidence from 19 midwifery training institutions, this study contributes empirical insights to the limited body of literature on digital readiness in midwifery education in low- and middle-income settings. The Digital Teaching Readiness Index (DTRI) offers a pragmatic benchmarking tool that may support institutional self-assessment and policy planning in this regard. As a simple, context-sensitive benchmarking framework, the DTRI may also support regulators, ministries of health and education, and training institutions in identifying priority investments and monitoring progress toward equitable digital capacity in midwifery education. Addressing the identified infrastructural and pedagogical constraints is essential to ensure that digital technologies enhance, rather than merely replicate, traditional models of teaching and to support the development of a competent and resilient midwifery workforce.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNMCN: Nursing and Midwifery Council of Nigeria, NHREC: National Health Research Ethics Committee of Nigeria, FGD: focus group discussion, IDI: in-depth interviews, ICM: International Confederation of Midwives, LSTM: Liverpool School of Tropical Medicine\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Ethical approval for the study was obtained from the Liverpool School of Tropical Medicine Research Ethics Committee, United Kingdom (Approval reference: 24-074) and the National Health Research Ethics Committee of Nigeria (Approval reference: NHREC/01/01/2007-10/02/2025). All participants provided informed consent prior to participation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The datasets generated and/or analysed during the current study are not publicly available due to ethical and confidentiality considerations but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This study was funded by the Bill \u0026amp; Melinda Gates Foundation (Investment ID: INV-084839). The funder had no role in the study design, data collection, analysis, interpretation of data, or decision to publish the findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;HMA: Conceptualization; Methodology; Investigation; Project administration; Data curation; Writing \u0026ndash; original draft; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eHM: Conceptualization; Methodology; Supervision; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eANL: Conceptualization; Methodology; Formal analysis; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eSW: Formal analysis; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eIG: Interpretation of findings; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eMAL: Interpretation of findings; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eOE: Interpretation of findings; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eFD: Methodology; Data collection tools development; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eCM: Methodology; Data collection tools development; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eABB: Project administration; Investigation; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eNA: Institutional oversight; Technical guidance; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eYT: Institutional oversight; Technical guidance; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eCAA: Conceptualization; Methodology; Supervision; Funding acquisition; Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors thank the participating midwifery institutions, educators, preceptors and students for sharing their experiences and views. The authors also acknowledge the support of the Gates Foundation and implementing partners under the MAMII project.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMelisa M, Susanti AI. Digitalizing midwifery education: trends, tools, and transformation. Curricula J Curric Dev. 2025;4(1):633\u0026ndash;648.\u003c/li\u003e\n\u003cli\u003eKhatatbeh H, Amer F, Ali AM, ALBashtawy M, Kurnianto A, Abu-Abbas M, et al. Challenges of distance learning encountering nursing students after the COVID-19 pandemic: a study from the Middle East. BMC Nurs. 2024;23(1):574.\u003c/li\u003e\n\u003cli\u003eNurhayati S, Bimantoro S, Ahsan MH. Digital technology in midwifery education and training: advancing competences and clinical practices. Int J Educ Curric Appl. 2025;8:115.\u003c/li\u003e\n\u003cli\u003eBerg E, Lepp M. The meaning and application of student-centered learning in nursing education: an integrative review of the literature. Nurse Educ Pract. 2023;69:103622.\u003c/li\u003e\n\u003cli\u003eJobst S, Lindwedel U, Marx H, Pazouki R, Ziegler S, K\u0026ouml;nig P, et al. Competencies and needs of nurse educators and clinical mentors for teaching in the digital age: a multi-institutional cross-sectional study. BMC Nurs. 2022;21(1):240.\u003c/li\u003e\n\u003cli\u003eGeraghty S, Bromley A, Bull A, Dube M, Turner C. Millennial midwifery: online connectivity in midwifery education. Nurse Educ Pract. 2019;39:26\u0026ndash;31.\u003c/li\u003e\n\u003cli\u003eSaini M, Sengupta E, Singh M, Singh H, Singh J. Sustainable Development Goal for quality education (SDG 4): a study to extract the pattern of association among SDG 4 indicators employing a genetic algorithm. Educ Inf Technol. 2023;28(2):2031\u0026ndash;2069.\u003c/li\u003e\n\u003cli\u003eNdayisenga JP, Babenko-Mould Y, Kasine Y, Nkurunziza A, Mukamana D, Murekezi J, et al. Blended teaching and learning methods in nursing and midwifery education: a scoping review. Res J Health Sci. 2021;9(1):100\u0026ndash;114.\u003c/li\u003e\n\u003cli\u003eGarti I, Tonto OS, Shikpup NJ, Gray M. Stakeholder perspectives of the adoption and effectiveness of digital learning in midwifery education in Africa: a scoping review. SAGE Open Nurs. 2025;11:23779608251380333.\u003c/li\u003e\n\u003cli\u003eBalasubramaniam S, Manni SM, Bhargava S, Agrawal N, Asif R, Chawngthu L, et al. Blending virtual with conventional learning to improve student midwifery skills in India. Nurse Educ Pract. 2018;28:163\u0026ndash;167.\u003c/li\u003e\n\u003cli\u003eDowner T, Gray M, Capper T. Online learning and teaching approaches used in midwifery programs: a scoping review. Nurse Educ Today. 2021;103:104980.\u003c/li\u003e\n\u003cli\u003eInternational Confederation of Midwives. ICM global standards for midwifery education (revised 2021) [Internet]. The Hague: ICM; 2021 [cited 2025 Mar]. Available from: https://internationalmidwives.org/resources/global-standards-for-midwifery-education/\u003c/li\u003e\n\u003cli\u003eLadjar YFL, Susanti AI. Effectiveness of technology in midwifery education for enhancing knowledge and clinical skills. Inov Kurikulum. 2024;21(4):1995\u0026ndash;2008.\u003c/li\u003e\n\u003cli\u003eNukunu F, Odoi P, Boateng VO, Donkor W, Bennin L, Addy A. The journey to digitalization: the story of nursing and midwifery training colleges in Ghana. Ghana J Nurs Midwifery. 2024;1(1):1\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eEgilsdottir H\u0026Ouml;, Heyn LG, Falk RS, Brembo EA, Byermoen KR, Moen A, et al. Factors associated with changes in students\u0026rsquo; self-reported nursing competence after clinical rotations: a quantitative cohort study. BMC Med Educ. 2023;23(1):107.\u003c/li\u003e\n\u003cli\u003eRyht\u0026auml; I, Elonen I, Saaranen T, Sormunen M, Mikkonen K, K\u0026auml;\u0026auml;ri\u0026auml;inen M, et al. Social and health care educators\u0026rsquo; perceptions of competence in digital pedagogy: a qualitative descriptive study. Nurse Educ Today. 2020;92:104521.\u003c/li\u003e\n\u003cli\u003eMbombi MO, Bopape MA, Ravele T, Ntho TA, Muthelo L, Phukubye TA, et al. Applying an e-learning framework to explore learner nurses\u0026rsquo; and nurse educators\u0026rsquo; perceptions about technology platforms in nursing. PLoS One. 2025;20(3):e0312681.\u003c/li\u003e\n\u003cli\u003eHarerimana A, Wicking K, Biedermann N, Yates K. Integrating nursing informatics into undergraduate nursing education in Africa: a scoping review. Int Nurs Rev. 2021;68(3):420\u0026ndash;433.\u003c/li\u003e\n\u003cli\u003eAchampong EK. Assessing the current curriculum of the nursing and midwifery informatics course at nursing and midwifery institutions in Ghana. J Med Educ Curric Dev. 2017;4:2382120517706890.\u003c/li\u003e\n\u003cli\u003eEddy IN, Nyengidiki T, Ani G, Asagba P, Eleke C. Digital technologies used in nursing education: a systematic review of educators\u0026rsquo; perspectives. J Nurs Midwifery Allied Health Sci. 2025;3(1):8\u0026ndash;12.\u003c/li\u003e\n\u003cli\u003eAddae HY, Alhassan A, Issah S, Azupogo F. Online learning experiences among nursing and midwifery students during the COVID-19 outbreak in Ghana: a cross-sectional study. Heliyon. 2022;8(12):e12155.\u003c/li\u003e\n\u003cli\u003eNsemo A. Perception, experiences and challenges of online and virtual learning during COVID-19 pandemic among student midwives of the Garden City University College, Kenyase-Kumasi, Ghana. Middle East J Res Educ Soc Sci. 2022.\u003c/li\u003e\n\u003cli\u003eAkalin A, D\u0026rsquo;haenens F, Vermeulen J, Tricas-Sauras S, Lanssens D. Using digital technologies and applications in midwifery practice in Belgium: a descriptive cross-sectional study. Midwifery. 2025;140:104218.\u003c/li\u003e\n\u003cli\u003eHolden RJ, Karsh BT. The technology acceptance model: its past and its future in health care. J Biomed Inform. 2010;43(1):159\u0026ndash;172.\u003c/li\u003e\n\u003cli\u003eOwoeye ID, Chipps JA, Daniels F. Nurse educators\u0026rsquo; competence and use of digital education technology at selected nursing education institutions in Nigeria. Int J Afr Nurs Sci. 2025;23:100870.\u003c/li\u003e\n\u003cli\u003eIshaq MN, Walugembe F. Perception of teachers and students towards the use of e-learning management system in Gombe State College of Nursing, Nigeria. SSRN Electron J. 2022. https://doi.org/10.2139/ssrn.4183443.\u003c/li\u003e\n\u003cli\u003eUNFPA, ICM, WHO. State of the world\u0026rsquo;s midwifery 2021: building a health workforce to meet the needs of women, newborns and adolescents everywhere [Internet]. New York: UNFPA; 2021 [cited 2026 Feb 11]. Available from: https://www.unfpa.org/sites/default/files/pub-pdf/21-038-UNFPA-SoWMy2021-Report-ENv4302.pdf\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Digital technology, midwifery education, e-learning, mixed methods, Nigeria, health workforce training, Digital Teaching Readiness Index","lastPublishedDoi":"10.21203/rs.3.rs-9085369/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9085369/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDigital transformation in health professions education is often framed as a matter of technology adoption and educator attitudes. However, in low-resource settings, institutional enabling conditions may play a more decisive role in determining whether digital tools can be meaningfully integrated into teaching practice. This study assessed digital teaching readiness in pre-service midwifery institutions in Nigeria and examined how structural capacity shapes the adoption of digital technologies in education.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA convergent parallel mixed-methods design was used. Nineteen midwifery training institutions across five geopolitical zones were assessed using a structured institutional checklist administered electronically via REDCap. Qualitative data included 13 in-depth interviews with educators and preceptors, three focus group discussions with 25 students, and 37 teaching observations. A Digital Teaching Readiness Index (DTRI; 0\u0026ndash;100) was constructed from five components: student Internet access, computer laboratories/library computers, projector availability, learning management system (LMS) use, and observed ICT use during teaching. Quantitative data were analysed descriptively, and associations between student\u0026ndash;educator ratios and DTRI scores were explored using Spearman rank correlation. Qualitative data were analysed thematically.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eDigital infrastructure was limited. Five institutions (26.3%) provided student Internet access, eight (42.1%) had functional computer laboratories/library computers, and one (5.3%) reported LMS use. ICT use was observed in 6 of 37 teaching sessions (16.2%). DTRI scores ranged from 0 to 60: eleven institutions (57.9%) scored\u0026thinsp;\u0026lt;\u0026thinsp;20, two (10.5%) scored 20\u0026ndash;39, and six (31.6%) scored 40\u0026ndash;60. Student\u0026ndash;educator ratios varied widely (8:1\u0026ndash;282:1) and were moderately negatively correlated with DTRI scores (ρ \u0026asymp; \u0026minus;0.58). Qualitative findings highlighted unreliable electricity, limited equipment, and funding constraints as key barriers to digital implementation.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eDigital integration in Nigerian midwifery education is constrained less by attitudinal resistance than by institutional capacity limitations. Addressing infrastructure, governance alignment, and educator support is critical for sustainable digital adoption. The DTRI provides a practical benchmarking tool for assessing digital readiness in similar low-resource training environments.\u003c/p\u003e","manuscriptTitle":"Digital readiness in Nigerian midwifery education: a mixed-methods study of 19 training institutions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 07:12:23","doi":"10.21203/rs.3.rs-9085369/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"251775987624193402073690119549865485965","date":"2026-05-04T18:23:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222269545261915705665046085597149227224","date":"2026-05-03T15:31:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54222618905857819952745281424524731277","date":"2026-05-02T14:01:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173832422025326557991139983078885312131","date":"2026-04-17T23:21:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T07:27:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T09:10:23+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-25T16:54:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-24T19:46:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Education","date":"2026-03-24T19:41:54+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b5c3922d-d431-4f62-a3d9-424312503721","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"251775987624193402073690119549865485965","date":"2026-05-04T18:23:44+00:00","index":70,"fulltext":""},{"type":"reviewerAgreed","content":"222269545261915705665046085597149227224","date":"2026-05-03T15:31:14+00:00","index":69,"fulltext":""},{"type":"reviewerAgreed","content":"54222618905857819952745281424524731277","date":"2026-05-02T14:01:11+00:00","index":68,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T07:12:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 07:12:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9085369","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9085369","identity":"rs-9085369","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}