Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools

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Methods The study employed a descriptive survey design to observe and analyse classroom interactions between teachers and students, focusing on verbal and non-verbal communication. Researchers used a structured observation schedule to collect data from a purposively selected sample of 10 mathematics teachers and 725 students across five schools. The researchers designed the instrument to collect information on teachers’ and students’ interaction patterns in the classroom. They analysed the data using mean scores, standard deviation, percentages, and t-test statistics, applying a 0.05 significance level for hypothesis testing. Findings The results of the analysis revealed that teachers dominate all the activities in the classroom; that is, the teachers were the active people in the classes, while the students were just passive listeners and moderate engagement through non-verbal behaviours. Statistical analysis showed significant differences between teacher and student patterns, particularly verbal behaviours. The study underscores that mathematics classes in senior secondary schools in the Festac area of Lagos State were teachers-centered. Conclusion Based on the study findings, the researchers recommended that mathematics teachers adopt more student-centered teaching approaches to enhance active student participation and engagement during lessons. Also, they should not be too strict, but they should be approachable, friendly, and accommodating so that the students will not be afraid to ask questions during or after the lesson, enhancing their performance. Hence, the government should ensure that teacher training programs incorporate observation techniques to effectively equip teachers with the skills to assess and improve classroom interaction. 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F1000Research 2025, 14 :1018 ( https://doi.org/10.12688/f1000research.166713.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] Opesemowo Oluwaseyi Aina Gbolade https://orcid.org/0000-0003-0242-7027 1 , Taiwo Olufunmi 2 , Alawaye Modupe 3 , Etobro Benjamin Apkesi 4 Opesemowo Oluwaseyi Aina Gbolade https://orcid.org/0000-0003-0242-7027 1 , Taiwo Olufunmi 2 , Alawaye Modupe 3 , Etobro Benjamin Apkesi 4 PUBLISHED 02 Dec 2025 Author details Author details 1 Mathematics, Science and Technology Education, University of Johannesburg Faculty of Education, Auckland Park, Gauteng, South Africa 2 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria 3 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria 4 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria Opesemowo Oluwaseyi Aina Gbolade Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Taiwo Olufunmi Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Alawaye Modupe Roles: Conceptualization, Data Curation, Formal Analysis, Methodology Etobro Benjamin Apkesi Roles: Data Curation, Writing – Original Draft Preparation OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Objective This study examined the application of Modified Flanders Interaction Analysis during mathematics lessons in senior secondary schools in the Festac area of Lagos State, Nigeria. Methods The study employed a descriptive survey design to observe and analyse classroom interactions between teachers and students, focusing on verbal and non-verbal communication. Researchers used a structured observation schedule to collect data from a purposively selected sample of 10 mathematics teachers and 725 students across five schools. The researchers designed the instrument to collect information on teachers’ and students’ interaction patterns in the classroom. They analysed the data using mean scores, standard deviation, percentages, and t-test statistics, applying a 0.05 significance level for hypothesis testing. Findings The results of the analysis revealed that teachers dominate all the activities in the classroom; that is, the teachers were the active people in the classes, while the students were just passive listeners and moderate engagement through non-verbal behaviours. Statistical analysis showed significant differences between teacher and student patterns, particularly verbal behaviours. The study underscores that mathematics classes in senior secondary schools in the Festac area of Lagos State were teachers-centered. Conclusion Based on the study findings, the researchers recommended that mathematics teachers adopt more student-centered teaching approaches to enhance active student participation and engagement during lessons. Also, they should not be too strict, but they should be approachable, friendly, and accommodating so that the students will not be afraid to ask questions during or after the lesson, enhancing their performance. Hence, the government should ensure that teacher training programs incorporate observation techniques to effectively equip teachers with the skills to assess and improve classroom interaction. READ ALL READ LESS Keywords Classroom interaction, students’ participation, Flander interaction analysis categories system, modified Flanders interaction analysis, mathematics lessons. Corresponding Author(s) Opesemowo Oluwaseyi Aina Gbolade ( [email protected] ) Close Corresponding author: Opesemowo Oluwaseyi Aina Gbolade Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2025 Aina Gbolade OO et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Aina Gbolade OO, Olufunmi T, Modupe A and Benjamin Apkesi E. Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.12688/f1000research.166713.2 ) First published: 01 Oct 2025, 14 :1018 ( https://doi.org/10.12688/f1000research.166713.1 ) Latest published: 02 Dec 2025, 14 :1018 ( https://doi.org/10.12688/f1000research.166713.2 ) Revised Amendments from Version 1 This revised version of the article incorporates substantial improvements in structure, methodological clarity, and theoretical alignment compared to the previously published version. The Methods section has been significantly expanded to include a detailed explanation of observer training procedures and inter-rater reliability, which were not previously fully described. The revised manuscript now outlines the three-phase training programme, calibration exercises, certification process, and the statistical reliability indices (percentage agreement and Cohen’s kappa), thereby strengthening the methodological rigour of the study. Additional enhancements were made to the description of the Modified Flanders Interaction Analysis (MFIA) instrument. The ten behavioural categories have now been clearly defined, and the specific modifications made for the study’s context are explicitly stated. This provides greater transparency, allowing readers to understand precisely how teacher–student interactions were coded. The Observation Protocol has also been expanded to clarify lesson duration, number of observations per teacher, and scheduling procedures, ensuring replicability and methodological coherence. Minor edits were made throughout the manuscript to enhance readability, reduce redundancy, and eliminate duplicate references. These revisions do not alter the study’s original findings but substantially improve the clarity, methodological robustness, and scholarly contribution of the manuscript. This revised version of the article incorporates substantial improvements in structure, methodological clarity, and theoretical alignment compared to the previously published version. The Methods section has been significantly expanded to include a detailed explanation of observer training procedures and inter-rater reliability, which were not previously fully described. The revised manuscript now outlines the three-phase training programme, calibration exercises, certification process, and the statistical reliability indices (percentage agreement and Cohen’s kappa), thereby strengthening the methodological rigour of the study. Additional enhancements were made to the description of the Modified Flanders Interaction Analysis (MFIA) instrument. The ten behavioural categories have now been clearly defined, and the specific modifications made for the study’s context are explicitly stated. This provides greater transparency, allowing readers to understand precisely how teacher–student interactions were coded. The Observation Protocol has also been expanded to clarify lesson duration, number of observations per teacher, and scheduling procedures, ensuring replicability and methodological coherence. Minor edits were made throughout the manuscript to enhance readability, reduce redundancy, and eliminate duplicate references. These revisions do not alter the study’s original findings but substantially improve the clarity, methodological robustness, and scholarly contribution of the manuscript. See the authors' detailed response to the review by Torang Siregar READ REVIEWER RESPONSES Introduction The effectiveness of classroom instruction considerably depends on the quality of interaction between teachers and students. To foster meaningful classroom interaction in mathematics lessons is essential for enhancing deep learning and critical thinking. Engaging students through collaborative and active learning strategies not only aids in understanding abstract concepts but also promotes higher-order thinking skills ( Dominguez, 2024 ; Firdaus & Satriawan, 2025 ). The conventional teaching methods in many Nigerian secondary schools, including those in Lagos State, often rely on teacher-centered approaches that limit student participation and engagement. This raises concerns about students’ conceptual understanding and academic performance in mathematics ( Opesemowo, 2025a ), the subject usually regarded as challenging and intimidating. Implementing more interactive teaching methods like group work, discussions, and hands-on activities could help mitigate these concerns and foster a more collaborative learning environment. By encouraging students to engage actively with the material and each other, teachers can promote better retention of concepts and greater problem-solving skills ( Mukhtoralieva, 2025 ; Xayrullayevna, 2024 ). This shift towards student-centered learning in mathematics classrooms in Lagos State can improve academic performance and cultivate a deeper appreciation and positive attitudes towards the subject among students. Flander Interaction Analysis Categories System (FIACS), a structured framework for observing and analysing verbal communication in classrooms, was developed by Flanders (1970) . This system categorises interactions into distinct types, allowing educators to effectively assess the dynamics of teacher-student communication ( Novianti & Anugrawati, 2023 ). It classifies classroom interactions into teacher talk, student talk, and silence. FIACS has been widely adopted in educational research for assessing instructional practices and promoting more balanced teacher-student interaction ( Ayunda et al., 2021 ; Nafisah & Setianingsih, 2024 ). However, the original FIACS was developed within a Western educational context ( Flanders, 1970 ), and its application in diverse settings such as Nigeria has unveiled certain limitations. This has led to the development and adoption of Modified Flanders Interaction Analysis (MFIA), which adapts the original framework to suit better local classroom realities, including larger class sizes, cultural norms, and varying levels of student preparedness. The MFIA aims to categorise all the verbal actions that can be found in this study. The aim is to promote implementing the Flanders process in the educational process in schools, as the quantity and consistency of teacher-student interaction is a vital element of effective teaching and improved learning in the classroom. In Nigeria, several studies have shown that classroom interactions are heavily dominated by teacher talk, often exceeding 80% of total communication, leaving minimal space for students’ inquiry, discussion, and exploration ( Agbarakwe & Ona, 2024 ). This imbalance limits the development of critical thinking, problem-solving skills, and learner autonomy competencies increasingly emphasised in modern educational frameworks as required for 21st-century success. Mathematics, in particular, demands active student engagement, frequent feedback, and dialogue to clarify misconceptions and reinforce learning. The application of MFIA offers a promising strategy to address these challenges by providing teachers with actionable insights into their communication patterns and enabling instructional adjustments that promote more student-centered practices. When properly implemented, MFIA can be a reflective tool for teachers to evaluate their interaction styles, increase student talk time, and foster a more inclusive and participatory learning environment. In the context of Lagos State, where senior secondary schools face varied educational challenges, including overcrowded classrooms and heterogeneous student backgrounds, applying MFIA during mathematics lessons may help bridge the gap between instructional intent and learning outcomes. The teachers-students’ interaction was so poor that students could not freely relate with their teachers one-on-one. Another problem is the teacher-to-student ratio because of the large population of students. The higher the population, the more difficult it is for the teacher to have individual rapport with the students. Hence, most students lacked proper monitoring to understand the subject. According to Olayinka and Olayinka (2023) , students’ attitudes toward mathematics significantly influence their performance, with negative attitudes often leading to poor outcomes. Mathematics is a fascinating subject, but some teachers know how to teach but do not know what to teach, while others know what to teach but do not know how to teach. These two sets of teachers will make mathematics difficult for students. A good mathematics teacher must know what to teach and how to teach. With this, his students will excel and develop a positive attitude towards the subject. However, some teachers today belong to the formal category and either know how or what to teach. Basically, teachers play a pivotal role in shaping the students’ knowledge by understanding and managing the dynamic processes that influence student outcomes. Multiple factors determine these outcomes, including subject knowledge, instructional strategies, teaching experience, attitudes toward mathematics, professional development, and classroom climate. Recent studies highlight that effective teaching practices significantly impact students’ interest, self-efficacy, and achievement in mathematics ( Iwintolu et al., 2024 ; Zhu & Kaiser, 2022 ). Aligning instruction with students’ cognitive processes fosters a more profound understanding and promotes meaningful learning ( Kelly et al., 2023 ; Opesemowo, 2025a ). Moreover, student-centered pedagogical approaches that encourage active engagement, critical thinking, and problem-solving have also been shown to enhance academic performance. The successful implementation of such strategies depends on continuous professional development and institutional support ( Kong & Wang, 2024 ). Rather than simply transmitting knowledge, teachers act as facilitators of learning, guiding students through structured and interactive lessons. Tools like the MFIA help mathematics teachers reflect on classroom communication patterns and improve instructional practices, ultimately supporting better learning outcomes in mathematics. Despite its potential, limited empirical studies have examined the use of MFIA in Nigerian secondary schools, especially within the subject area of mathematics. This study, therefore, seeks to explore the application of MFIA during mathematics lessons in senior secondary schools in Lagos State. Thus, an analysis of classroom interaction could provide a sensitive means of exposing how specific patterns in classroom verbal interaction reveal ways the teacher simulates and guides student learning. Hence, this study examines classroom interaction between teachers and students during mathematics lessons in senior secondary schools. Strategies for teaching Mathematics The choice of teaching method is critical to instructional effectiveness and highly depends on the teacher’s understanding of individual student differences ( Felder & Brent, 2005 ). Understanding students’ diverse cognitive, emotional, and learning styles significantly enhances teachers’ ability to diversify instructional strategies. This insight allows teachers to tailor their teaching methods to better meet their students’ varied needs, ultimately advancing a more effective learning environment ( Babatimehin et al., 2025 ; Opesemowo, 2024 ; Ramdani et al., 2022 ). Adopting varied teaching strategies can significantly enhance student engagement and learning outcomes in contemporary classrooms, especially in subjects like mathematics, where abstract reasoning is paramount ( Alam & Mohanty, 2024 ; Bray & Tangney, 2016 ; Rehman et al., 2024 ). Teaching strategies often employed include the lecture method, which helps present large volumes of information; the laboratory method, which encourages hands-on learning and experimentation; and field trip methods, which help connect theoretical concepts to real-world experiences. Other commonly used approaches are the discussion methods, which foster interactive learning; the test method for assessment and feedback; and the problem-solving method, which promotes analytical thinking. Furthermore, the analytical, discovery, and expository methods cater to student independence levels and curriculum demands ( Magnusson & Zackariasson, 2019 ; Opesemowo et al., 2024 ). Mathematics teachers are therefore encouraged to adopt a flexible and reflective approach to teaching methods, aligning them with students’ needs, subject objectives, and classroom dynamics to promote effective and inclusive learning experiences. Statement of the problem The persistent underachievement of students in mathematics within Nigerian secondary schools remains a significant concern. Despite various interventions, national examination results, such as those from the West African Examinations Council (WAEC) and National Examinations Council (NECO), consistently indicate low proficiency levels among mathematics students ( Akinpelu et al., 2024 ; Babatimehin et al., 2025 ). This trend is particularly evident in Lagos State, where students’ performance in mathematics continues to lag behind expectations. A critical examination of teaching methodologies reveals a predominant reliance on teacher-centered approaches, characterised by rote learning and minimal student engagement. Such methods often neglect the diverse learning needs of students and fail to foster critical thinking skills essential for mathematical problem-solving ( Awofala, 2017 ). Moreover, traditional assessment techniques, primarily through questionnaires and test scores, provide limited insight into the actual classroom dynamics and the quality of teacher-student interactions. ( Akinpelu et al., 2024 ). In addition, observational studies employing tools like FIACS have highlighted the dominance of teacher talks over student participation in classrooms. For instance, a study conducted at the Federal College of Education (Technical), Omoku, Rivers State, Nigeria, found that teacher talk accounted for approximately 83.43% of classroom interaction, and student talk was a mere 12.71% ( Agbarakwe & Ona, 2024 ). Such imbalances in classroom interactions can hinder the development of a conducive learning environment and impede students’ mathematical understanding. Given these challenges, a pressing need exists to explore and implement more interactive, student-centered teaching strategies in mathematics lessons. The application of MFIA during mathematics lessons offers a promising avenue to assess and enhance classroom interactions, potentially improving student engagement and performance in mathematics. Purpose of the study To assess the classroom interaction pattern of teaching and learning mathematics in Amuwo-Odofin Local Government of Lagos. Specifically, the study examined whether mathematics class was student-centered or teacher-centered and the adequacy of classroom interaction between the teachers and the students. Research questions 1. What percentage of the time is spent on each classroom activity? 2. What percentage of the time is spent on each classroom behaviour? Research hypotheses 1. There is no significant difference between the verbal behaviour of teachers and students. 2. There is no significant difference between the non-verbal behaviour of teachers and students. 3. There is no significant difference between the time of interaction of teachers and students. Methodology This study adopted a descriptive survey research design, which is appropriate for systematically observing and describing the interaction patterns between teachers and students during classroom instruction ( Creswell & Creswell, 2017 ). This approach allows researchers to capture the nuances of verbal exchanges and the dynamics of classroom interactions, providing insight into how this pattern influences learning outcomes. Population The target population was comprised of mathematics teachers and students in the Festac area, Lagos State, Nigeria. The study sample consisted of 10 mathematics teachers and 725 students from five public secondary schools in the Festac area of Lagos State, Nigeria. We utilised a purposive sampling technique to select the participants, targeting schools with an existing record of consistent mathematics instruction and an adequate student population in the state. Instrument The study employed the MFIA instrument ( https://doi.org/10.5281/zenodo.17049546 ) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Data collection The study analysed the collected data quantitatively using descriptive statistics such as mean scores, standard deviation, and percentages to identify trends in teacher-student interaction. Additionally, inferential statistics, specifically the t-test, were used to determine the significance of observed differences at the 0.05 significance level. These statistical methods ensure a robust interpretation of findings and allow the researcher to conclude the effectiveness of classroom interaction patterns on students’ learning experiences in mathematics. Observer training and reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided practice and calibration exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and field simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-rater reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. Results Question 1: What percentage of the time is spent on each classroom activity? The results for the analysis of the percentage of the time spent are given in Table 1 . Table 1. Time spent on each classroom activity. S/N Class activities Time spent in minutes Percentage 1 Praise and encouragement 1 2.50 2 Asking questions about content 1.50 3.75 3 Teaching 14.50 30.50 4 Give direction 0.80 2.00 5 Student responds to teacher 4.40 11.00 6 The teacher responds to the student 0.80 2.00 7 Teacher non-verbal behaviour (writing and drawing) 6.60 16.50 8 Students non-verbal behaviour 6.10 15.25 9 Silence in the class 0.60 1.50 10. Confusion - noise in the class 3.60 9.00 Table 1 analyses the distribution of instructional time across various classroom activities during mathematics lessons. The highest proportion of time (14.50), 30.50%, was devoted to direct teaching, indicating a teacher-centered approach dominated the classroom interaction, which aligns with conventional instructional practices in mathematics lessons. This was followed by teacher non-verbal behaviour, such as writing and drawing on the board, which accounted for 16.5% of classroom time, and student non-verbal behaviour, which constituted 15.25%. These findings suggest that a significant portion of the lesson was devoted to individual cognitive engagement, albeit largely passive. The student responses to teacher questions represented 11.0% of the observed time, indicating moderate verbal student participation. Conversely, teacher responses to students and giving directions were relatively low, each accounting for only 2.0%, implying limited dialogic interaction or feedback within the lesson. Other forms of teacher talk, such as praise and encouragement (2.5%) and content-related questioning (3.75%), were used sparingly, potentially reducing opportunities for formative assessment and student motivation. The classroom also experienced 3.6 minutes of confusion or noise and 0.6 minutes of silence, suggesting occasional disruptions that may affect instructional efficiency. Finally, the time allocation reflects a predominantly teacher-based classroom with limited interactive and feedback-driven engagement, highlighting the need for more student-centered approaches that could promote active student engagement, increased dialogue and diversified instructional strategies to support meaningful learning. Question 2: What percentage of the time is spent on each classroom behaviour? Data was analysed using the classroom activities tables, which were regrouped into four: teacher verbal behaviour, teachers’ non-verbal behaviour, students’ verbal behaviour and students’ non-verbal behaviour. The time slice allotted to each classroom is shown in Table 2 . Table 2. Time spent on classroom behaviour. S/N Classroom behaviour Time spent in minute Percentage 1 Teachers’ verbal 17.90 44.75 2 Students’ verbal 8.80 22.00 3 Teachers’ non-verbal 6.60 16.5 4 Students’ non-verbal 6.70 16.75 Table 2 shows time spent on classroom behaviour during mathematics lessons. The data indicates that teachers’ verbal behaviour dominates, occupying 44.75% of classroom time, reflecting a teacher-centered instructional style. Students’ verbal behaviour accounts for 22%, suggesting moderate student participation but limited dialogic interaction. Non-verbal behaviours are almost equally distributed, with teachers’ non-verbal behaviour at 16.5% and students’ non-verbal behaviour at 16.75%, indicating shared time spent on tasks such as writing or working independently. Hypothesis 1: There is no significant difference between the verbal behaviour of teachers and students. Table 3 presents a t-test comparison of the verbal behaviour of teachers and students during mathematics lessons. The result shows that teachers had a higher mean verbal behaviour score (M = 17.90, SD = 3.03) than students (M = 5.20, SD = 1.62). The calculated t-value (t = 11.087) exceeds the critical t-value (t = 2.262) at df = 9 and p < 0.05, indicating a statistically significant difference. Therefore, we rejected the null hypothesis. This suggests that teachers dominate classroom verbal interactions significantly more than students, reinforcing a teacher-centered communication pattern. Hypothesis 2: There is no significant difference between the non-verbal behaviour of teachers and students. Table 3. To test this hypothesis, a t-test comparison of the verbal behaviour of teachers and students. Variable N X SD df t.cal. t.table remark Verbal behaviour of teachers 10 17.90 3.027 9 11.087 2.262 Rejected Verbal behaviour of students 10 5.20 1.619 * P < 0.05. Table 4 shows the independent t-test of the non-verbal behaviour of teachers and students during classroom instruction. The mean score (M = 6.60, SD = 1.647) for teachers’ non-verbal behaviour is higher than the student’s (M = 6.10, SD = 2.283). The calculated t-value (t = 0.745) is less than the critical t-value (t = 2.262) at df = 9 and 0.05 significant level, indicating that the difference is not statistically significant. Therefore, the null hypothesis is accepted, suggesting that teachers and students engage in non-verbal classroom behaviours at comparable levels. Table 4. To test this hypothesis, a t-test comparison of the non-verbal behaviour of teachers and students. Variable N X SD df t.cal. t.table Remark Non-verbal behaviour of teachers 10 6.60 1.647 9 0.745 2.262 Accepted Non-verbal behaviour of students 10 6.10 2.283 * P < 0.05. Table 5 presents a t-test comparison of the interaction time between teachers and students during classroom instruction. The mean interaction time for teachers is 24.50 minutes, while that of students is 11.30 minutes. The calculated t-value (t = 8.337) exceeds the critical value (t = 2.262) at df = 9 and p < 0.05 significant level, indicating a statistically significant difference. Hence, we rejected the null hypothesis. This result suggests that teachers dominate classroom interaction time, highlighting a teacher-centered instructional pattern with limited student participation. Table 5. T-test table of interaction time between teachers and students. Variable N X SD df t.cal t.table Remark Interaction time of teachers 10 24.50 4.301 9 8.337 2.262 Rejected Interaction time of students 10 11.30 3.199 * P < 0.05. Discussion This study is based on the application of MFIA, offering valuable insights into classroom interaction patterns during mathematics instruction in Lagos State senior secondary schools. The results collectively point to a predominantly teacher-centered approach, with limited student verbal engagement and interaction. This study observed that teachers spend much of class time engaging in verbal instruction. This aligns with the findings of Burgess et al. (2020) , who emphasised that heavy reliance on teacher talk can diminish opportunities for student engagement, critical thinking, and mathematical discourse. While helpful in delivering content, such dominance may hinder deeper understanding, especially if not complemented by student-centered learning activities. Similarly, Blatchford et al. (2011) noted that when teachers dominate classroom talk, students are often relegated to passive roles, limiting their active capacity, participation and intellectual autonomy. Subsequently, students’ verbal contributions were relatively minimal compared to their teachers. This finding is consistent with Chen et al. (2020) , who argued that restricted student talk time can result in lower cognitive engagement and hinder the development of mathematical reasoning. Moreover, low verbal participation may reflect classroom culture where students are not encouraged or supported to voice their ideas, a concern also highlighted by Ho et al. (2023) in their study on silence over the wire: student verbal participation and the virtual classroom in the digital era. While some cultural norms may discourage verbal participation, Karjanto (2019) stresses the importance of gradually scaffolding students toward more active classroom involvement, even in traditionally teacher-centered contexts. Teachers and students exhibited relatively balanced non-verbal behaviour, including writing, drawing, and not-taking. This parity reflects mutual involvement in academic tasks, suggesting that non-verbal engagement is more equitably distributed while verbal interaction may be one-sided. Ijaz et al. (2023) have argued that teachers’ effective use of non-verbal cues like gestures and visual aids can significantly enhance student comprehension. However, Valenzeno et al. (2003) caution that ambiguous or mismatched non-verbal gestures can confuse students, stressing the need for purposeful use of such cues. Therefore, teachers must be mindful of their non-verbal communication in the classroom, as it plays a key role in facilitating student learning and understanding. By being intentional and transparent with their gestures and visual aids, teachers can create a more engaging and effective learning environment for their students. Ultimately, the combination of verbal and non-verbal communication in the classroom can lead to improved academic performance and student success. The disparity in the overall interaction time between teachers and students further confirms the teacher-dominated nature of classroom discussions. Research by Lo and Chen (2021) suggests that students benefit more from learning environments where their voices are integral to the instructional process. When the teacher-centered approach monopolises classroom time, opportunities for students to develop problem-solving skills, articulate reasoning, and collaborate with peers are constrained. To create a more student-centered learning environment, teachers should actively seek input from their students and provide opportunities for them to engage in discussions and activities that promote critical thinking and collaboration. By allowing students to take more ownership of their learning experiences, teachers can help facilitate the development of essential skills that are crucial for success in both academic and real-world settings. Encouraging active participation and valuing the perspectives of each student can lead to a more inclusive and dynamic educational experience for everyone involved. Conclusion The result of the study showed that teaching mathematics in senior secondary school has not completely weaned itself from the historical antecedent in which teachers dominated classroom activities. Again, the study highlights a significant imbalance in teacher-student interactions during mathematics lessons, with teachers occupying the dominant communicative role. While non-verbal communication engagement is more balanced, the lack of substantial student verbal participation raises concerns about the effectiveness of current teaching practices in fostering deep understanding and critical thinking. To address these issues, teachers should adopt dialogic teaching strategies, leverage technological tools to promote participation and engage in professional development focused on enhancing classroom discourse. Such measures are essential for creating learning environments that support active student engagement and improved learning outcomes in mathematics lessons. Recommendations Based on the findings of this study, we recommended that: • Mathematics teachers should not be too strict and must be friendly, approachable, and accommodating so that the students will not be afraid to ask questions during and after the lesson. • Classroom observational techniques have gained worldwide recognition in developed and developing countries, and the government should make efforts to include observational techniques in teacher training institutions. • In-service teachers’ seminars should be organised for such teachers to expose them to the implications of classroom interaction. • Workshops, seminars, training, and conferences should be organised regularly to enhance professional development. Limitations and suggestions for further study This study was limited to a small number of secondary schools within the Festac area of Lagos State, Nigeria, which restricts the generalizability of the findings to other educational contexts. The purposive sampling method and reliance on observational data, time constraint and reliance on single data may have introduced bias and failed to capture deeper cognitive or affective aspects of classroom interaction. In addition, the study focused solely on mathematics lessons, excluding other subject areas that might offer comparative insights. For further research, broader samples across diverse regions and subjects are recommended. Incorporating mixed methods, such as interviews and student feedback, could provide richer insights into the dynamics of classroom interaction. Ethical statement Ethical approval for this study was obtained from the Faculty of Education Ethics Committee at Lagos State University, Ojo, Nigeria. The study ethical number is Ethical Clearance Number: S E M 3-2 0 2 5-1 2 3 4. The study was conducted in compliance with the principles outlined in the Declaration of Helsinki. All participants were fully informed about the purpose, scope, and procedures of the research before data collection commenced. Informed consent was obtained from each participant, ensuring their voluntary participation. To safeguard confidentiality, all responses were anonymized, and personal identifiers were removed. The data were treated with strict confidentiality, and measures were taken to ensure that participants’ privacy, dignity, and trust were maintained throughout the study. Informed consent As part of the research process, we obtained written informed consent from all participants prior to data collection. The participants in this study were senior secondary students aged 18 years and above and therefore were not minors. Each participant was fully informed about the purpose of the study, the voluntary nature of their participation, and their right to withdraw at any time without penalty. They were also assured that the information provided would be used strictly for research purposes, that their identities would remain confidential, and that all data would be anonymised during analysis and reporting. Since no minors were involved in the study, parental or guardian consent and child assent were not applicable. By ensuring full transparency and respecting participants’ rights, the research process upheld the principles of ethical integrity and maintained participants’ trust, thereby strengthening the overall credibility of the study. Clinical trial number Not applicable. Data availability statement Zenodo data MFIA_Date set https://doi.org/10.5281/zenodo.15698071 ( Opesemowo, Oluwaseyi Aina Gbolade, 2025b ) MFIA Questionnaire https://doi.org/10.5281/zenodo.17049546 ( Opesemowo, Oluwaseyi Aina Gbolade, 2025c ) Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). 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Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 01 Oct 2025 ADD YOUR COMMENT Comment Author details Author details 1 Mathematics, Science and Technology Education, University of Johannesburg Faculty of Education, Auckland Park, Gauteng, South Africa 2 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria 3 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria 4 Educational Foundations and Counselling Psychology, Lagos State University Faculty of Education, Ojo, Lagos, Nigeria Opesemowo Oluwaseyi Aina Gbolade Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Taiwo Olufunmi Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Alawaye Modupe Roles: Conceptualization, Data Curation, Formal Analysis, Methodology Etobro Benjamin Apkesi Roles: Data Curation, Writing – Original Draft Preparation Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 02 Dec 2025, 14:1018 https://doi.org/10.12688/f1000research.166713.2 version 1 Published: 01 Oct 2025, 14:1018 https://doi.org/10.12688/f1000research.166713.1 Copyright © 2025 Aina Gbolade OO et al . This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Aina Gbolade OO, Olufunmi T, Modupe A and Benjamin Apkesi E. Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.12688/f1000research.166713.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Version 2 VERSION 2 PUBLISHED 02 Dec 2025 Revised Views 0 Cite How to cite this report: Ukobizaba F. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r439353 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-439353 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 10 Jan 2026 Fidele Ukobizaba , African Centre of Excellence for Innovative Teaching and Learning Mathematics and Science (ACEITLMS), University of Rwanda College of Education, Kayonza, Rwanda Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.192113.r439353 The revised manuscript shows clear improvement across several sections. The presentation of results is now more organized and easier to follow. However, some points need to be addressed before acceptance for indexing. First, the results ... Continue reading READ ALL The revised manuscript shows clear improvement across several sections. The presentation of results is now more organized and easier to follow. However, some points need to be addressed before acceptance for indexing. First, the results in Table 2 are under objective 2. Yet, Table 2 came before. Thus, Table 2 should come after objective 2. Second, the remark in Table 4 was to accept null hypothesis (H0). Yet, it was shown that the p-value is less than 0.05. Which means that the H0 is to be rejected. Third, the computed p-values for Table 3,4, and 5 should be presented in tables. Fourth, the conclusion made (first recommendation) should be removed since there are not findings supporting it. Once the above points have been adequately addressed, the article will be improved for coherence, readability, and academic rigor. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: Mathematics Education, applied calculus, hands on activities in mathematics, project-based learning, mathematics pedagogy, and educational research methods. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Ukobizaba F. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r439353 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-439353 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Kuzu TE. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r443413 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-443413 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 09 Jan 2026 Taha Ertuğrul Kuzu , University of Education Schwäbisch Gmünd, Schwäbisch Gmünd, Germany Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.192113.r443413 Review for the article with the title Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools Dear authors, ... Continue reading READ ALL Review for the article with the title Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools Dear authors, thank you for the opportunity to review your article „Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools“. In my opinion, the manuscript addresses a relevant and empirically important issue, namely classroom interaction patterns in senior secondary mathematics classrooms in Lagos State, and it is commendable that you seek to adapt an established observational instrument to a specific local context. In the following, I focus my review on the introduction and research gap, the theoretical and conceptual framing (especially regarding FIACS/MFIA), the method, and the empirical insights, with particular attention to points where the argumentation could be sharpened or deepened. With regard to the introduction and research gap , you convincingly motivate the general relevance of classroom interaction for learning processes in mathematics and situate your study within concerns about teacher-centred instruction in Nigerian secondary schools. For example, you argue that “the conventional teaching methods in many Nigerian secondary schools… often rely on teacher-centered approaches that limit student participation and engagement” . At this point, however, a very critical reader might perceive a risk of confirmatory bias: teacher-centredness is introduced early on as a defining characteristic of the context and as a pedagogical problem, while the empirical analysis that follows primarily serves to document and reaffirm this assumption rather than to interrogate it in a more differentiated or open-ended manner. I would therefore suggest omitting or at least substantially weakening this assumption at the introductory stage, as it is not yet empirically substantiated at the point at which it is introduced. Leaving the question of teacher-centredness more open in the introduction would allow the empirical analysis to function more clearly as an exploratory investigation rather than as a confirmation of a prior claim. Another issue is that the introduction remains somewhat broad and normative in tone, and the specific research gap could be articulated more sharply. While you state that “limited empirical studies have examined the use of MFIA in Nigerian secondary schools, especially within the subject area of mathematics” , it would strengthen the paper to specify more clearly what is not yet known: Is it the mere distribution of talk, the balance between verbal and non-verbal behaviour, or the didactical quality of interaction patterns in mathematics classrooms? At present, the reader is led quite early toward the expectation that teacher-centredness (whatever that means, see below) is problematic per se (and expectable, see above), but the analytical added value of documenting this again remains somewhat implicit. What would clearly strengthen the article is a (more) explicit definition of “teacher-centredness” . It would be important to clarify under which conditions an interaction pattern or instructional process is classified as teacher-centred and, equally, when this label may not be appropriate. In particular, a high proportion of teacher turns does not necessarily indicate teacher-centred instruction in a didactically problematic sense. For example, a high proportion of teacher talk does not necessarily indicate transmissive or authoritarian instructional practices; it may instead reflect supportive or process-oriented functions such as “Giving Directions” (FIACS Category 4). From a didactical perspective, this form of interaction – even if it occurs in a high amount – can constitute a meaningful and pedagogically justified form of instructional support, rather than an indicator of reduced learning quality (because of being too „teacher-centered“). Without such conceptual clarification, there is a risk that teacher-centredness is equated too directly with the sheer quantity of teacher talk, rather than being interpreted in relation to the function and quality of the respective interactional moves. This leads directly to the theoretical background and conceptual framing , particularly concerning FIACS and its modification. You correctly outline FIACS as a framework focusing on verbal classroom interaction and acknowledge that it was developed in a Western context. You also state that MFIA was “modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common” (p. 5). From a conceptual perspective, this sentence is problematic in two ways. First, it risks circularity: teacher-dominated instruction is described as a “reality” that motivates the modification of the instrument, and the study then empirically shows that instruction is teacher-dominated. Second, the notion of “modification” itself remains underspecified on a theoretical level. While you later list and clearly define the ten categories used in MFIA, these categories largely correspond to the original FIACS categories, albeit with refined labels and the explicit inclusion of non-verbal behaviour. A more explicit discussion of what is theoretically gained by calling this an expanded or modified version would be helpful. Is the modification primarily empirical-pragmatic, or does it also imply a different understanding of classroom interaction? At present, the (critical) reader may ask: What exactly is modified beyond contextual relabelling and the inclusion of non-verbal behaviour? Relatedly, while you rightly mention common critiques of FIACS indirectly by noting its focus on interaction quantity, the manuscript could benefit from a more explicit engagement with these limitations. FIACS (and MFIA) primarily capture what happens in terms of interaction distribution , not why it happens or how cognitively demanding or didactically meaningful teacher moves are. This limitation becomes particularly relevant in light of your conclusions (see below). Turning to the method , the revised version has clearly improved in transparency and rigour. The detailed description of observer training, calibration, and inter-rater reliability (with κ = 0.81) is a clear strength of the manuscript. The observation protocol, lesson duration, and number of observations per teacher are also clearly specified. One point that remains conceptually underdeveloped, however, concerns the analytical scope of the method. Given that MFIA codes interaction at one-minute intervals and aggregates frequencies and percentages, the design is inherently descriptive. This is not a weakness per se, but it should be acknowledged more explicitly as a methodological boundary. At several points, the text implicitly suggests that interaction patterns can be linked to (deeper) learning processes (e. g., when stating that „applying MFIA during mathematics lessons may help bridge the gap between instructional intent and learning outcomes“ ), yet the method does not allow access to cognitive activation, quality of feedback, or students’ meaning-making processes. This becomes most evident in the empirical results and their interpretation . Your key finding – that teachers dominate verbal classroom interaction while students are largely passive listeners with moderate non-verbal engagement – is clearly presented and statistically well supported. For instance, you show that teachers’ verbal behaviour accounts for 44.75% of classroom time compared to 22% for students. However, the central interpretive question remains: What do we actually gain from knowing that instruction is labelled as “teacher-centred” on this basis? As a reader, I miss a deeper engagement with the quality and function of teacher talk. Your own Table 1 differentiates between various types of teacher interaction, such as “Direct Teaching/Lecturing” (30.50%) and “Giving Directions” (2.00%) on the one hand, and more dialogic categories like “Content-Related Questioning” (3.75%) and “Teacher Response to Students” (2.00%) on the other. These distributions are highly informative, yet they are not analysed in depth or interpreted didactically. In addition, one aspect that may confuse readers concerns the category “Criticism and Authority Cues” . While this category is introduced as part of the MFIA framework on page 6, it does not appear explicitly in Table 1. This raises the question of whether this category was empirically absent or whether it was subsumed under another category. If the former is the case, the implication would be that no critical or authority-based teacher behaviour occurred at all, which seems implausible and therefore requires clarification. From a didactical perspective, it makes a crucial difference whether teacher dominance consists primarily of high-quality explanations, cognitively activating questions, or scaffolding feedback, or whether it is mainly organisational, directive, or authority-based talk. As you note in passing, categories such as “Giving Directions” and “Teacher Response to Students” occur relatively rarely, but the implications of this are not fully unpacked. Without such an analysis, the conclusion that teaching is teacher-centred risks remaining descriptively correct (if only the speaking percentages/ turn-taking amount is considered) but educationally underspecified. Teacher-centredness can mean very different things in mathematics education: it may involve carefully designed impulses aimed at cognitive conflict and conceptual change, or it may consist of procedural instruction focused on right and wrong answers without engaging with students’ learning processes. This issue also affects your recommendations and discussion. You conclude that teachers should adopt “more student-centered teaching approaches to enhance active student participation”. While this aligns with curriculum ideals and international standards, it is important to clarify that more student talk or participation does not automatically imply higher cognitive activation. Increasing the quantity of student turns without attention to task quality, mathematical substance, or feedback processes may result in superficial participation. Your own data could be used more productively by discussing which MFIA categories should be strengthened from a didactical standpoint and for what reasons. For example, interactional moves classified as “Giving Directions” could be deliberately expanded if the aim is to establish a more process-oriented and supportive feedback culture in the classroom, rather than merely increasing the overall amount of student or teacher talk. Finally, regarding the limitations , it is positive that you explicitly acknowledge that the study “may have introduced bias and failed to capture deeper cognitive or affective aspects of classroom interaction” and suggest mixed-methods approaches for future research. I would encourage you to be even more explicit here: cognitive aspects are not merely imperfectly captured by MFIA; they are largely outside the analytical scope of the instrument. Stating this more clearly would not weaken the study but rather position it more honestly as a descriptive, observation-based contribution that can inform further, more process-oriented research. In sum, the study is methodologically careful and empirically solid in documenting interaction patterns, but its analytical and didactical contribution would be significantly strengthened by (a) a clearer conceptualisation of what is modified in MFIA, (b) a deeper analysis of the quality of teacher talk using your own category system, and (c) a more nuanced discussion of what “teacher-centred” and “student-centred” mean from a learning-theoretical perspective. Addressing these points would greatly enhance the explanatory power and educational relevance of the manuscript. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests: No competing interests were disclosed. Reviewer Expertise: Mathematics Education, Multilingualism/ Translanguaging, Interaction Analysis, Primary Education, Digital Media in Education I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Kuzu TE. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r443413 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-443413 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 01 Oct 2025 Views 0 Cite How to cite this report: Siregar T. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.183745.r432297 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v1#referee-response-432297 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 22 Nov 2025 Torang Siregar , UIN Syekh Ali Hasan Ahmad Addary Padangsidimpuan, Sumatra, Indonesia Approved VIEWS 0 https://doi.org/10.5256/f1000research.183745.r432297 Final Assessment and Required Revisions Overall, this is a valuable contribution to educational research in Nigeria, highlighting persistent challenges in classroom interaction during mathematics instruction. The study addresses an important gap and uses a recognized analytical framework. Points ... Continue reading READ ALL Final Assessment and Required Revisions Overall, this is a valuable contribution to educational research in Nigeria, highlighting persistent challenges in classroom interaction during mathematics instruction. The study addresses an important gap and uses a recognized analytical framework. Points That Must Be Addressed Before Acceptance : Clarify the MFIA Categories Used: Provide a list of the 10 behavioral categories adapted in the study, explaining any modifications from the original FIACS. Detail Observer Training and Reliability: Describe how observers were trained and whether inter-rater reliability was measured (e.g., percentage agreement or Cohen’s kappa). Specify Observation Protocol: State how many lessons were observed per teacher, total observation duration, and scheduling (e.g., single or multiple days). Improve Citation Formatting: Ensure all references follow a consistent style (APA) and remove duplicates or formatting errors. Link Instrument to Text: Mention the questionnaire DOI in the Methods section, not just in data availability. Once these issues are resolved, the article will be scientifically robust and suitable for indexing. Recommendation : Accept after Minor Revisions Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Mathematics Education, Educational Technology Integration, Discovery Learning Models, Critical Thinking in Mathematics, Meta-Analysis in Education, Computer-Assisted Mathematics Learning, Mathematics Education, Educational Technology Integration, Discovery Learning Models, Critical Thinking in Mathematics, Meta-Analysis in Education, Computer-Assisted Mathematics Learning I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Siregar T. Reviewer Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.183745.r432297 ) The direct URL for this report is: https://f1000research.com/articles/14-1018/v1#referee-response-432297 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 02 Dec 2025 Oluwaseyi Opesemowo , Mathematics, Science and Technology Education, University of Johannesburg Faculty of Education, Auckland Park, South Africa 02 Dec 2025 Author Response Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. ... Continue reading Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Observer Training and Reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA Categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided Practice and Calibration Exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and Field Simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-Rater Reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation Protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Observer Training and Reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA Categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided Practice and Calibration Exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and Field Simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-Rater Reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation Protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. Competing Interests: No conflict of interest was reported by the authors. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 02 Dec 2025 Oluwaseyi Opesemowo , Mathematics, Science and Technology Education, University of Johannesburg Faculty of Education, Auckland Park, South Africa 02 Dec 2025 Author Response Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. ... Continue reading Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Observer Training and Reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA Categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided Practice and Calibration Exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and Field Simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-Rater Reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation Protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Observer Training and Reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA Categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided Practice and Calibration Exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and Field Simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-Rater Reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation Protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. Competing Interests: No conflict of interest was reported by the authors. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 01 Oct 2025 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 3 Version 2 (revision) 02 Dec 25 read read Version 1 01 Oct 25 read Torang Siregar , UIN Syekh Ali Hasan Ahmad Addary Padangsidimpuan, Sumatra, Indonesia Taha Ertuğrul Kuzu , University of Education Schwäbisch Gmünd, Schwäbisch Gmünd, Germany Fidele Ukobizaba , University of Rwanda College of Education, Kayonza, Rwanda Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Ukobizaba F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 10 Jan 2026 | for Version 2 Fidele Ukobizaba , African Centre of Excellence for Innovative Teaching and Learning Mathematics and Science (ACEITLMS), University of Rwanda College of Education, Kayonza, Rwanda 0 Views copyright © 2026 Ukobizaba F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions The revised manuscript shows clear improvement across several sections. The presentation of results is now more organized and easier to follow. However, some points need to be addressed before acceptance for indexing. First, the results in Table 2 are under objective 2. Yet, Table 2 came before. Thus, Table 2 should come after objective 2. Second, the remark in Table 4 was to accept null hypothesis (H0). Yet, it was shown that the p-value is less than 0.05. Which means that the H0 is to be rejected. Third, the computed p-values for Table 3,4, and 5 should be presented in tables. Fourth, the conclusion made (first recommendation) should be removed since there are not findings supporting it. Once the above points have been adequately addressed, the article will be improved for coherence, readability, and academic rigor. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise Mathematics Education, applied calculus, hands on activities in mathematics, project-based learning, mathematics pedagogy, and educational research methods. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Ukobizaba F. Peer Review Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r439353) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-439353 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2026 Kuzu T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 09 Jan 2026 | for Version 2 Taha Ertuğrul Kuzu , University of Education Schwäbisch Gmünd, Schwäbisch Gmünd, Germany 0 Views copyright © 2026 Kuzu T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Review for the article with the title Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools Dear authors, thank you for the opportunity to review your article „Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools“. In my opinion, the manuscript addresses a relevant and empirically important issue, namely classroom interaction patterns in senior secondary mathematics classrooms in Lagos State, and it is commendable that you seek to adapt an established observational instrument to a specific local context. In the following, I focus my review on the introduction and research gap, the theoretical and conceptual framing (especially regarding FIACS/MFIA), the method, and the empirical insights, with particular attention to points where the argumentation could be sharpened or deepened. With regard to the introduction and research gap , you convincingly motivate the general relevance of classroom interaction for learning processes in mathematics and situate your study within concerns about teacher-centred instruction in Nigerian secondary schools. For example, you argue that “the conventional teaching methods in many Nigerian secondary schools… often rely on teacher-centered approaches that limit student participation and engagement” . At this point, however, a very critical reader might perceive a risk of confirmatory bias: teacher-centredness is introduced early on as a defining characteristic of the context and as a pedagogical problem, while the empirical analysis that follows primarily serves to document and reaffirm this assumption rather than to interrogate it in a more differentiated or open-ended manner. I would therefore suggest omitting or at least substantially weakening this assumption at the introductory stage, as it is not yet empirically substantiated at the point at which it is introduced. Leaving the question of teacher-centredness more open in the introduction would allow the empirical analysis to function more clearly as an exploratory investigation rather than as a confirmation of a prior claim. Another issue is that the introduction remains somewhat broad and normative in tone, and the specific research gap could be articulated more sharply. While you state that “limited empirical studies have examined the use of MFIA in Nigerian secondary schools, especially within the subject area of mathematics” , it would strengthen the paper to specify more clearly what is not yet known: Is it the mere distribution of talk, the balance between verbal and non-verbal behaviour, or the didactical quality of interaction patterns in mathematics classrooms? At present, the reader is led quite early toward the expectation that teacher-centredness (whatever that means, see below) is problematic per se (and expectable, see above), but the analytical added value of documenting this again remains somewhat implicit. What would clearly strengthen the article is a (more) explicit definition of “teacher-centredness” . It would be important to clarify under which conditions an interaction pattern or instructional process is classified as teacher-centred and, equally, when this label may not be appropriate. In particular, a high proportion of teacher turns does not necessarily indicate teacher-centred instruction in a didactically problematic sense. For example, a high proportion of teacher talk does not necessarily indicate transmissive or authoritarian instructional practices; it may instead reflect supportive or process-oriented functions such as “Giving Directions” (FIACS Category 4). From a didactical perspective, this form of interaction – even if it occurs in a high amount – can constitute a meaningful and pedagogically justified form of instructional support, rather than an indicator of reduced learning quality (because of being too „teacher-centered“). Without such conceptual clarification, there is a risk that teacher-centredness is equated too directly with the sheer quantity of teacher talk, rather than being interpreted in relation to the function and quality of the respective interactional moves. This leads directly to the theoretical background and conceptual framing , particularly concerning FIACS and its modification. You correctly outline FIACS as a framework focusing on verbal classroom interaction and acknowledge that it was developed in a Western context. You also state that MFIA was “modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common” (p. 5). From a conceptual perspective, this sentence is problematic in two ways. First, it risks circularity: teacher-dominated instruction is described as a “reality” that motivates the modification of the instrument, and the study then empirically shows that instruction is teacher-dominated. Second, the notion of “modification” itself remains underspecified on a theoretical level. While you later list and clearly define the ten categories used in MFIA, these categories largely correspond to the original FIACS categories, albeit with refined labels and the explicit inclusion of non-verbal behaviour. A more explicit discussion of what is theoretically gained by calling this an expanded or modified version would be helpful. Is the modification primarily empirical-pragmatic, or does it also imply a different understanding of classroom interaction? At present, the (critical) reader may ask: What exactly is modified beyond contextual relabelling and the inclusion of non-verbal behaviour? Relatedly, while you rightly mention common critiques of FIACS indirectly by noting its focus on interaction quantity, the manuscript could benefit from a more explicit engagement with these limitations. FIACS (and MFIA) primarily capture what happens in terms of interaction distribution , not why it happens or how cognitively demanding or didactically meaningful teacher moves are. This limitation becomes particularly relevant in light of your conclusions (see below). Turning to the method , the revised version has clearly improved in transparency and rigour. The detailed description of observer training, calibration, and inter-rater reliability (with κ = 0.81) is a clear strength of the manuscript. The observation protocol, lesson duration, and number of observations per teacher are also clearly specified. One point that remains conceptually underdeveloped, however, concerns the analytical scope of the method. Given that MFIA codes interaction at one-minute intervals and aggregates frequencies and percentages, the design is inherently descriptive. This is not a weakness per se, but it should be acknowledged more explicitly as a methodological boundary. At several points, the text implicitly suggests that interaction patterns can be linked to (deeper) learning processes (e. g., when stating that „applying MFIA during mathematics lessons may help bridge the gap between instructional intent and learning outcomes“ ), yet the method does not allow access to cognitive activation, quality of feedback, or students’ meaning-making processes. This becomes most evident in the empirical results and their interpretation . Your key finding – that teachers dominate verbal classroom interaction while students are largely passive listeners with moderate non-verbal engagement – is clearly presented and statistically well supported. For instance, you show that teachers’ verbal behaviour accounts for 44.75% of classroom time compared to 22% for students. However, the central interpretive question remains: What do we actually gain from knowing that instruction is labelled as “teacher-centred” on this basis? As a reader, I miss a deeper engagement with the quality and function of teacher talk. Your own Table 1 differentiates between various types of teacher interaction, such as “Direct Teaching/Lecturing” (30.50%) and “Giving Directions” (2.00%) on the one hand, and more dialogic categories like “Content-Related Questioning” (3.75%) and “Teacher Response to Students” (2.00%) on the other. These distributions are highly informative, yet they are not analysed in depth or interpreted didactically. In addition, one aspect that may confuse readers concerns the category “Criticism and Authority Cues” . While this category is introduced as part of the MFIA framework on page 6, it does not appear explicitly in Table 1. This raises the question of whether this category was empirically absent or whether it was subsumed under another category. If the former is the case, the implication would be that no critical or authority-based teacher behaviour occurred at all, which seems implausible and therefore requires clarification. From a didactical perspective, it makes a crucial difference whether teacher dominance consists primarily of high-quality explanations, cognitively activating questions, or scaffolding feedback, or whether it is mainly organisational, directive, or authority-based talk. As you note in passing, categories such as “Giving Directions” and “Teacher Response to Students” occur relatively rarely, but the implications of this are not fully unpacked. Without such an analysis, the conclusion that teaching is teacher-centred risks remaining descriptively correct (if only the speaking percentages/ turn-taking amount is considered) but educationally underspecified. Teacher-centredness can mean very different things in mathematics education: it may involve carefully designed impulses aimed at cognitive conflict and conceptual change, or it may consist of procedural instruction focused on right and wrong answers without engaging with students’ learning processes. This issue also affects your recommendations and discussion. You conclude that teachers should adopt “more student-centered teaching approaches to enhance active student participation”. While this aligns with curriculum ideals and international standards, it is important to clarify that more student talk or participation does not automatically imply higher cognitive activation. Increasing the quantity of student turns without attention to task quality, mathematical substance, or feedback processes may result in superficial participation. Your own data could be used more productively by discussing which MFIA categories should be strengthened from a didactical standpoint and for what reasons. For example, interactional moves classified as “Giving Directions” could be deliberately expanded if the aim is to establish a more process-oriented and supportive feedback culture in the classroom, rather than merely increasing the overall amount of student or teacher talk. Finally, regarding the limitations , it is positive that you explicitly acknowledge that the study “may have introduced bias and failed to capture deeper cognitive or affective aspects of classroom interaction” and suggest mixed-methods approaches for future research. I would encourage you to be even more explicit here: cognitive aspects are not merely imperfectly captured by MFIA; they are largely outside the analytical scope of the instrument. Stating this more clearly would not weaken the study but rather position it more honestly as a descriptive, observation-based contribution that can inform further, more process-oriented research. In sum, the study is methodologically careful and empirically solid in documenting interaction patterns, but its analytical and didactical contribution would be significantly strengthened by (a) a clearer conceptualisation of what is modified in MFIA, (b) a deeper analysis of the quality of teacher talk using your own category system, and (c) a more nuanced discussion of what “teacher-centred” and “student-centred” mean from a learning-theoretical perspective. Addressing these points would greatly enhance the explanatory power and educational relevance of the manuscript. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Partly Competing Interests No competing interests were disclosed. Reviewer Expertise Mathematics Education, Multilingualism/ Translanguaging, Interaction Analysis, Primary Education, Digital Media in Education I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. reply Respond to this report Responses (0) Kuzu TE. Peer Review Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.192113.r443413) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1018/v2#referee-response-443413 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2025 Siregar T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. 22 Nov 2025 | for Version 1 Torang Siregar , UIN Syekh Ali Hasan Ahmad Addary Padangsidimpuan, Sumatra, Indonesia 0 Views copyright © 2025 Siregar T. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions. format_quote Cite this report speaker_notes Responses (1) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Final Assessment and Required Revisions Overall, this is a valuable contribution to educational research in Nigeria, highlighting persistent challenges in classroom interaction during mathematics instruction. The study addresses an important gap and uses a recognized analytical framework. Points That Must Be Addressed Before Acceptance : Clarify the MFIA Categories Used: Provide a list of the 10 behavioral categories adapted in the study, explaining any modifications from the original FIACS. Detail Observer Training and Reliability: Describe how observers were trained and whether inter-rater reliability was measured (e.g., percentage agreement or Cohen’s kappa). Specify Observation Protocol: State how many lessons were observed per teacher, total observation duration, and scheduling (e.g., single or multiple days). Improve Citation Formatting: Ensure all references follow a consistent style (APA) and remove duplicates or formatting errors. Link Instrument to Text: Mention the questionnaire DOI in the Methods section, not just in data availability. Once these issues are resolved, the article will be scientifically robust and suitable for indexing. Recommendation : Accept after Minor Revisions Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Partly Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Mathematics Education, Educational Technology Integration, Discovery Learning Models, Critical Thinking in Mathematics, Meta-Analysis in Education, Computer-Assisted Mathematics Learning, Mathematics Education, Educational Technology Integration, Discovery Learning Models, Critical Thinking in Mathematics, Meta-Analysis in Education, Computer-Assisted Mathematics Learning I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (1) Author Response 02 Dec 2025 Oluwaseyi Opesemowo, Mathematics, Science and Technology Education, University of Johannesburg Faculty of Education, Auckland Park, South Africa Instrument The study employed the MFIA instrument (https://doi.org/10.5281/zenodo.17049546) to systematically capture teacher–student interaction patterns during mathematics instruction. This allows for categorising and analysing verbal and non-verbal communication in teaching-learning environments. The observational instrument, the classroom activity sheet, was used to gather data on classroom interactions at one-minute intervals during live mathematics lessons. The MFIA was adapted from the classic FIACS but modified to better reflect the realities of Nigerian mathematics classrooms, where teacher-dominated instruction, board work, and limited student-initiated talk are common. The MFIA used in this study retained the ten original FIACS behavioural categories but introduced contextual modifications. The categories are: (1) Praise and Encouragement – Teacher statements or gestures showing approval, motivation, or positive reinforcement. (2) Content-Related Questioning – Teacher questions directly related to mathematics concepts, procedures, or problem solving. (3) Direct Teaching/Lecturing – Explanations, demonstrations, worked examples, definitions, and conceptual exposition. (4) Giving Directions – Instructions relating to tasks, class activities, behaviour, or note-taking. (5) Teacher Response to Students – Clarifying, expanding, or giving feedback on student responses. (6) Criticism and Authority Cues – Statements reflecting correction of behaviour or implicit assertion of authority. (7) Teacher Non-Verbal Behaviour – Writing on the board, gesturing, using teaching aids, or other physical demonstrations. (8) Students non-verbal behaviour – Students answering teachers’ questions or giving short non-verbal responses. (9) Student-Initiated Talk – Questions, explanations, or ideas introduced spontaneously by students. (10) Confusion and Noise – Pauses, classroom noise, disruptions, or uncertainty during instruction. Observer Training and Reliability To ensure accuracy, consistency, and credibility in applying the Modified Flanders Interaction Analysis (MFIA) instrument during classroom observations, two observers underwent a structured training programme prior to data collection. The training process was conducted over two weeks and consisted of three sequential phases designed to familiarise observers with the MFIA categories and strengthen their coding precision. Phase 1: Familiarisation with MFIA Categories Observers were introduced to the ten behavioural categories adapted for the study, with emphasis on distinguishing verbal and non-verbal behaviours. They reviewed sample video lessons, practised identifying teacher and student behaviours, and discussed coding boundaries to ensure shared understanding of all category definitions. Phase 2: Guided Practice and Calibration Exercises Observers independently coded the same set of practice lessons at one-minute intervals and later compared results. Discrepancies were discussed and resolved collaboratively, enabling the observers to refine their decision rules and achieve a uniform interpretation of the MFIA categories. Calibration continued until agreement was consistently above the acceptable threshold for observational studies. Phase 3: Certification and Field Simulation Before proceeding to live classroom observations, each observer completed a certification exercise by coding two additional mathematics lesson videos. These were compared against a master coding guide prepared by an experienced MFIA user. Only after demonstrating acceptable accuracy were they approved for field data collection. Inter-Rater Reliability To quantify agreement between observers during the pilot stage, percentage agreement and Cohen’s kappa (κ) were computed. Across all MFIA categories, observers achieved: • Percentage Agreement: 87% • Cohen’s Kappa (κ): 0.81 A kappa coefficient above 0.80 indicates strong inter-rater reliability, confirming that the observers consistently applied the MFIA coding scheme. Any minor inconsistencies identified were resolved prior to the commencement of formal data collection. This process ensured that the observational data collected during classroom visits were both reliable and valid for analysis. Observation Protocol Each teacher was observed teaching two separate mathematics lessons, allowing for comparison of interaction patterns across different content areas and classroom conditions. Each lesson observation lasted 40 minutes, consistent with the standard lesson duration in the participating schools. Observations were scheduled across two different days for each teacher to minimise the influence of one-off events and to capture more stable behavioural patterns. The observation schedule was arranged in collaboration with school administrators to ensure that lessons selected reflected typical classroom practice rather than special or pre planned activities. This approach provided a total observation time of 80 minutes per teacher, generating sufficient data for reliable MFIA coding and analysis. View more View less Competing Interests No conflict of interest was reported by the authors. reply Respond Report a concern Siregar T. Peer Review Report For: Application of Modified Flanders Interaction Analysis During Mathematics Lessons in Lagos State Senior Secondary Schools [version 2; peer review: 1 approved, 2 approved with reservations] . F1000Research 2025, 14 :1018 ( https://doi.org/10.5256/f1000research.183745.r432297) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/14-1018/v1#referee-response-432297 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions Adjust parameters to alter display View on desktop for interactive features Includes Interactive Elements View on desktop for interactive features Competing Interests Policy Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. 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