Classroom Video Research Articles

The expertise of novices: A framework for prospective teacher’s noticing of children’s mathematical thinking

The purpose of this study was to articulate nuances within the process of learning to notice and to provide a framework for characterizing the capabilities of noticing in prospective mathematics teachers. We collected and analyzed data on teacher noticing based on classroom videos from prospective teachers in a mathematics content course. We analyzed data in accordance with existing research-based frameworks on noticing and in consideration with literature on expertise. We provide the Framework for the Expertise of Noticing, which describes noticing expertise along five dimensions: Evidence-based Noticing; Concrete vs. Abstract Characteristics in Noticing; Individual vs. Pattern Focus in Noticing; Task vs. Contextualized Perspective in Noticing; and Cognitive vs. Metacognitive Characteristics in Noticing. The framework is a tool for mathematics education researchers and teacher educators who study and support the development of noticing in prospective teachers.

The potential of classroom video recordings in detecting the TA-to-pupil, teacher-to-TA and peer interactions: An overview

Technology in the classroom comes in many shapes to differentiate instruction, create meaningful learning experiences, actively engage the learners, or inform about classroom exchanges. Video recordings are no exception. They facilitate the investigation of classroom interactions and the collection of audio-visual data that provide further insights into the teaching practice and classroom dynamics. Previous education research has almost turned a blind eye to uncovering the intricacies of elementary classroom behavior and interactions through the medium of modern technologies. Only scattered attempts have brought to bear the issue. To this end, this paper presents an overview of the salient role of digital technologies, mainly video materials, in clarifying the different interactions that take place within the confines of the classroom, including teacher-to-teaching assistant (TA) relationships, teacher-aide-to-pupil interactions, and peer-to-peer interaction drawing on an ongoing data collection from elementary schools around Hradec Králové (HK) region in the Czech Republic. Classroom recordings might be a fountainhead for detailed, reflective analysis, enhanced communication among all participants, and better teaching-learning practice if used properly. The first part of the paper reviews some related definitions based on several previous theoretical grounds. Then, it highlights the peculiar classroom interactions aided by various analytic angles. Deeply rooted in education research, these dynamics are indebted to the presence of audio and visual records. Most importantly, the paper is built around the research endeavor by researchers at the University of HK, mainly the Faculty of Education, that aims at getting down to brass tacks of TAs interactions by means of technological intervention in data collection (video recordings) and measurement (Flanders et al. – FIAS). Keywords: Video recordings, TA-to-Pupil interaction, Teacher-to-TA interaction, elementary schools, Flanders Interaction Analysis System

Research on Knowledge Tracing-Based Classroom Network Characteristic Learning Engagement and Temporal-Spatial Feature Fusion

To accurately assess students’ cognitive state of knowledge points in the learning process within the smart classroom, a knowledge tracing (KT) model based on classroom network characteristic learning engagement and temporal-spatial feature fusion (CL-TSKT) is proposed. First, a classroom network is constructed based on the information of the student ID, seating relationship, student–student interaction, head-up or head-down state, and classroom network characteristics obtained from a smart classroom video. Second, a learning engagement model is established by utilizing the student–student interactions, head-up or head-down state, and classroom network characteristics. Finally, according to the learning engagement model and the knowledge point test data, a parallel temporal attention GRU network is proposed. It is utilized to extract the temporal features of the knowledge points and learning engagement. They are fused to obtain the knowledge point-learning engagement temporal characteristics and their associated attributes. Meanwhile, a CNN is used to extract the knowledge point-knowledge point spatial features. We consider the associative properties of knowledge point-knowledge points from a spatial perspective and fuse the knowledge point-knowledge point spatial features with the knowledge point-learning engagement temporal features. To accurately characterize the cognitive state of the knowledge points and provide effective support for teachers’ accurate and sustainable interventions for learners in the teaching and learning process, this paper conducts extensive experiments on four real datasets. The CL-TSKT model in this paper shows superior performance in all four evaluation metrics, compared with the state-of-the-art KT models.

Situating Teacher Movement, Space, and Relationships to Pedagogy: A Visual Method and Framework

In conversations about pedagogy, researchers often overlook how physical space and movement shape teacher sensemaking. This article offers a comparative case study of classroom videos using a dynamic visual method to map embodied interaction called “interaction geography.” Our analysis proposes an integrative framework to study classroom interactions and teacher movement over space and time comprised of four salient characteristics within lessons: trails, landmarks, material routines, and circulation patterns. We discuss how this visual method and framework can be used and expanded by classroom researchers and teachers as a starting point to better understand teaching as a situative and spatial practice, a crucial step in characterizing responsive forms of instruction. This work has implications not only for teachers and teacher educators but also for architects, administrators, and researchers concerned with the physical design of classrooms.

From Raw Video to Pedagogical Insights: A Unified Framework for Student Behavior Analysis

Understanding student behavior in educational settings is critical in improving both the quality of pedagogy and the level of student engagement. While various AI-based models exist for classroom analysis, they tend to specialize in limited tasks and lack generalizability across diverse educational environments. Additionally, these models often fall short in ensuring student privacy and in providing actionable insights accessible to educators. To bridge this gap, we introduce a unified, end-to-end framework by leveraging temporal action detection techniques and advanced large language models for a more nuanced student behavior analysis. Our proposed framework provides an end-to-end pipeline that starts with raw classroom video footage and culminates in the autonomous generation of pedagogical reports. It offers a comprehensive and scalable solution for student behavior analysis. Experimental validation confirms the capability of our framework to accurately identify student behaviors and to produce pedagogically meaningful insights, thereby setting the stage for future AI-assisted educational assessments.

Expanding Education Researchers' Access to Classroom Observation Data With a Remote and Cost-Effective Video Data Collection Protocol.

The onset of the COVID-19 pandemic and associated long-term shifts to virtual instruction among most US schools presented notable challenges among education researchers. Ongoing projects conducted in school settings experienced sudden losses of access to teacher and student participants, in many cases leading to severe interruptions to data collection efforts. Perhaps most notably, upon returns to in-person instruction in the 2021/22 academic year most schools instigated strict policies limiting the number of non-school personnel who could enter school buildings, including researchers conducting in-person data collections. As such, many researchers had to find alternative means to gather data. In this paper, we offer a new protocol that we created in response to these challenges that allows for the secure and fully remote collection of video data in school settings. This new protocol not only addressed the immediate needs of the focal study but also addresses some of the most notable barriers to collecting classroom video data in the field of education research at large. In this paper, we describe the initial development and application of this protocol among a local study of elementary teachers, as well as the scaling of this protocol in a study of elementary teachers in multiple states. It is our hope that this protocol can expand education researchers', practitioners', and policymakers' access to classroom video data.

Exploring Attentional Dynamics in Animated Programming Environments: Trajectories, Variability, and Predictors

Researchers have proposed that the ability to pay attention to teachers’ instruction is a prerequisite for learning. However, meaningful learning is often challenged by the presence of rule-breaking behaviors. In this study, we argue that although students exhibit different attention-related behaviors in all instructional settings, some behaviors are unique to a typical classroom. It is still unclear what factors uniquely determine students’ attention-related behaviors in animated programming environments because of the paucity of research evidence in this area. This study investigates students’ attention-related behaviors during animated programming instruction, including attentional growth trajectory, the nature of differences in attention-related behaviors, and predictors of these behaviors. Our analysis involved 8 classroom videos that collected the programming activities of 30 university students in our previous study. The video files were annotated on a one-dimensional, continuous scale, yielding 1,920 timestamped data points. The data on attentional trajectories and differences in attention-related behaviors were analyzed using latent and multi-level growth modeling, respectively, while data focusing on the predictors of attentional processes were analyzed using the Random Forest machine learning algorithm. We found that students’ attentional growth trajectory is linear and accelerates toward on-task events. However, these behaviors vary within and between students, leading to differences in attention-related behaviors. The results also revealed that individual and instructional characteristics predict the differences in attention-related behaviors. The findings highlight the importance of structured topics, safe classroom environments, quality instructional support, and interactive multimedia objects that activate students’ memory, eliminate task difficulty, and reduce the amount of mental resources required for meaningful learning.

DA-ResNet: dual-stream ResNet with attention mechanism for classroom video summary

DA-ResNet: dual-stream ResNet with attention mechanism for classroom video summary

Learning from (re)experience: What mobile eye-tracking video can help us learn about the cognitive processes of teaching

IntroductionClassroom teachers need to monitor a group of students varying in interest, knowledge, and behavior at the same time that they present a lesson and adapt it on the fly to student questions and understanding. Many areas of expertise are associated with special kinds of perceptual skills, and teaching presents its own perceptual challenges. We discuss the special nature of the expert looking that teachers must develop and how it relates to more general models of expertise. Standard methods of classroom video are limited in their support of teacher professional looking, and we explore an alternative using mobile eyetracking that overcomes many of these limits. The combination of mobile eyetracking records and standard video enables the participant to “re-experience” a situation in a vivid way, while also seeing things they missed the first time through.MethodsWe report a study in which pairs of novice and experienced teachers teaching the same students watched their own mobile eyetracking recordings while performing a retrospective think-aloud task.ResultsExperienced teachers were better able to describe high-level features and their significance in the lessons, while novices were more likely to talk about in-the-moment events such as things they failed to see while teaching. This is consistent with work on expertise that suggests there are both costs and benefits to expert looking.DiscussionOur results suggest that the ability to quickly grasp the meaning of a classroom situation may be associated with less awareness of some of the lower-level features on which those inferences are based. Novice and experienced teachers notice different things and have different perspectives on classroom processes; understanding the cognitive process of teachers will require combining insights from each. The methods used in this study are quickly becoming less costly and more accessible, and they have a unique role to play in research and in teacher professional development.

Post-secondary classroom teaching quality evaluation using small object detection model

The classroom video has a complex background and dense targets. This study utilizes small object detection technology to analyze and evaluate students’ behavior in the classroom, aiming to objectively and accurately assess classroom quality. Firstly, noise is removed from the images using a median filter, and the contrast of the images is enhanced through histogram equalization. Label smoothing is applied to reduce the model’s sensitivity to labels. Then, features are extracted from the preprocessed images, and multi-scale feature fusion is employed to enhance semantic expression across multiple scales. Finally, a combination loss function is utilized to improve the accuracy of multi-object recognition tasks. Real-time detection of students’ behaviors in the classroom is performed based on the small object detection model. The average head-up rate in the classroom is calculated, and the quality of teaching is evaluated and analyzed. This study explores the methods and applications of small object detection technology based on actual teaching cases and analyzes and evaluates its effectiveness in evaluating the quality of higher education classroom teaching. The research findings demonstrate the significant importance of small object detection technology in effectively evaluating students’ learning conditions in higher education classrooms, leading to improved teaching quality and personalized education.

Streamlined Workforce Management System Using AI

In today's digital landscape, face recognition technology has emerged as a versatile and non-invasive tool used across sectors, despite its lower accuracy compared to iris or fingerprint recognition. Its applications range from security and authentication to optimizing attendance systems in educational institutions and workplaces. This paper introduces an innovative class attendance system employing face recognition technology, replacing manual processes prone to inaccuracies like proxy attendance. The system involves database creation from student images, utilizing Haar-Cascade classifiers for face detection, and Local Binary Pattern Histogram algorithms for live recognition from classroom video streams. It automates attendance data distribution to faculty members, enhancing efficiency and precision. Simultaneously, the security industry necessitates alert and vigilant security personnel to prevent breaches. A sophisticated hybrid system, leveraging machine learning techniques like OpenCV and EAR/MAR algorithms alongside UHD cameras, detects guard drowsiness and alerts them promptly using sound cues and preventive measures, ensuring continual vigilance. This innovative hybrid system fortifies security guard surveillance, mitigating potential vulnerabilities due to lapses in attentiveness. Key Word: Face Recognition Technology, Biometrics, Attendance Management, Security, Authentication, Surveillance, Machine Learning, Open CV, Security Guard Monitoring, Vigilance, Drowsiness Detection.

Individual learning paths mastering teachers’ professional vision

IntroductionPromoting a professional vision of teaching as a key factor of teachers’ expertise is a core challenge for teacher professionalization. While research on teaching has evolved and successfully evaluated various video-based intervention programs, a prevailing emphasis on outcome measures can yet be observed. However, the learning processes by which teachers acquire professional vision currently remain a black box. The current study sought to fill this research gap. As part of a course dedicated to promoting a professional vision of classroom management, students were imparted knowledge about classroom management that had to be applied to the analysis of authentic classroom videos. The study aimed to determine the variety of individual strategies that students applied during their video analyses, and to investigate the relationship between these and the quality of the students’ analyses, measured by their agreement with an experts’ rating of the video clips.MethodsThe sample comprised 45 undergraduate pre-service teachers enrolled in a course to acquire a professional vision of classroom management. By applying their imparted knowledge of classroom management, students engaged in the analysis of classroom videos to learn how to notice and interpret observable events that are relevant to effective classroom management. Implementing a learning analytical approach allowed for the gathering of process-related data to analyze the behavioral patterns of students within a digital learning environment. Video-based strategies were identified by conducting cluster analyses and related to the quality of the students’ analysis outcomes, measured by their concordance with the experts’ ratings.ResultsWe gained insight into the learning processes involved in video-based assignments designed to foster a professional vision of classroom management, such as the areas of interest that attracted students’ heightened attention. We could also distinguish different approaches taken by students in analyzing classroom videos. Relatedly, we found clusters indicating meticulous and less meticulous approaches to analyzing classroom videos and could identify significant correlations between process and outcome variables.DiscussionThe findings of this study have implications for the design and implementation of video-based assignments for promoting professional vision, and may serve as a starting point for implementing process-based diagnostics and providing adaptive learning support.

Preservice elementary teachers' perceptions of their science laboratory instructors in a phenomena‐based laboratory and how it impacts their conceptual development

AbstractPhenomena‐based approaches have become popular for elementary school teachers to engage children's innate curiosity in the natural world. However, integrating such phenomena‐based approaches in existing science courses within teacher education programs present potential challenges for both preservice elementary teachers (PSETs) and for laboratory instructors, both of whom may have had limited opportunities to learn or teach science within the student and instructor roles inherent within these approaches. This study uses a convergent parallel mixed‐methods approach to investigate PSETs' perceptions of their laboratory instructor's role within a Physical Science phenomena‐based laboratory curriculum and how it impacts their conceptual development (2 instructors/121 students). We also examine how the two laboratory instructors' discursive moves within the laboratory align with their's and PSETs' perceptions of the instructor role. Qualitative data includes triangulation between a student questionnaire, an instructor questionnaire, and video classroom observations, while quantitative data includes a nine‐item open response pre‐/post‐semester conceptual test. Guided by Mortimer's and Scott's analytic framework, our findings show that students primarily perceive their instructors as a guide/facilitator or an authoritarian/evaluator. Using Linn's knowledge integration framework, analysis of pre‐/post‐tests indicates that student outcomes align with students' perceptions of their instructors, with students who perceive their instructor as a guide/facilitator having significantly better pre‐/post‐outcomes. Additional analysis of scientific discourse from the classroom observations illustrates how one instructor primarily supports PSETs' perspectives on authentic science learning through dialogic–interactive talk moves whereas the other instructor epistemologically stifles personally relevant investigations with authoritative–interactive or authoritative–noninteractive discourse moves. Overall, this study concludes by discussing challenges facing laboratory instructors that need careful consideration for phenomena‐based approaches.

Exploring the Path of Innovative College Dance Teaching Models with Motion Capture Technology

Abstract The continuous development of artificial intelligence has brought new exploration paths and ideas for the teaching field, however, the current application and research of motion capture technology in college dance teaching mode is less. In this study, the human body and the appearance model are modeled in three dimensions: the simulated annealing particle swarm algorithm is used to optimize the human body modeling posture. Then, the feature vector matching algorithm is used to capture the human body’s movement posture, construct the college dance teaching mode, and carry out practical application. According to the study, the capture effect of the five movements in the dance teaching classroom video clip is between 0.865 and 0.945, and each movement is recognized with an accuracy of above 95%. After using this model, it was concluded by analyzing the effect of dance teaching that the number of excellent grades in the experimental group was 2 more than that in the control group, and the number of good grades was 2 more than that in the control group. This study provides a new development path for dance teaching in colleges and universities.

Understanding K‐3 Teachers' Literacy Instructional Practices During thePandemic‐Impacted2020–2021 School Year

AbstractThis instrumental case study is focused on understanding more about literacy instruction in K‐3 classrooms during the pandemic‐impacted 2020–2021 school year. The study aims to examine (a) how teachers described their literacy instruction before and during the COVID‐19 pandemic; (b) the types of literacy instructional practices teachers implemented across in‐person, virtual, and hybrid modalities; and (c) how teachers' implementation of these practices aligns with research on early grades literacy instruction. Data included classroom video of 25 teachers' literacy instruction, 162 classroom artifacts (e.g., student work samples), and statewide survey responses from 7110 teachers in spring 2020 and 5811 teachers in spring 2021. Teachers reported spending an average of 1 h less per week on literacy instruction in 2020–2021 as compared to a typical pre‐pandemic school year. Despite these reported declines in instructional time, teachers in all modalities were observed implementing literacy instructional practices at comparable rates as they reported prior to the pandemic. However, teachers' implementations of these practices varied widely, with some teachers providing research‐aligned literacy instruction while others did not. This range in quality was evident across modalities, including within the group of teachers providing in‐person instruction. Results from this study challenge existing theories about instructional time and modality that have been posed to explain the pandemic's negative impacts on elementary students' literacy outcomes.

Immersive insights: Unveiling the impact of 360-degree videos on preservice teachers’ classroom observation experiences and teaching-quality ratings

Classroom videos are commonly used to observe and assess teaching quality in both teacher education and research on teaching and learning. In recent years, traditional video environments have increasingly been complemented by 360-degree videos, which promise a more immersive and realistic classroom experience and may affect the teaching-quality ratings that result. The aim of the present study was to explore differences between immersive 360-degree and traditional video environments in preservice teachers' (PSTs') classroom observation experiences and teaching-quality ratings. Seventy-five PSTs observed two classroom videos: one using an immersive 360-degree video environment and one using a traditional video environment. For 360-degree videos, observers reported higher cognitive, affective, and physiological involvement in the classroom situation, higher motivation, and higher mental effort when making classroom observations. For one aspect of teaching quality (focus on key concepts), the observation-based ratings resulting from 360-degree videos were better aligned with experts’ assessments of the videos. Furthermore, the results showed that the differences between video environments remained significant after the novelty of VR technology was controlled for.

Eight Priorities for Instructional Videos in the Online Classroom

To enhance student engagement and learning in the online classroom, instructional videos need to be thoughtfully created, curated, and integrated. Key considerations include making the videos learner-centered and relevant, ensuring easy access, keeping video length short, focusing on clarity over perfection, providing alternative means of accessing the information, fostering student interaction, and personalizing videos to enhance the sense of class participation and connection.

Guiding pre-service teachers’ visual attention through instructional settings: an eye-tracking study

In complex classroom situations, pre-service teachers often struggle to identify relevant information. Consequently, classroom videos are widely used to support pre-service teachers’ professional vision. However, pre-service teachers need instructional guidance to attend to relevant information in classroom videos. Previous studies identified a specific task instruction and prompts as promising instructions to enhance pre-service teachers’ professional vision. This mixed-methods eye-tracking study aimed to compare pre-service teachers’ visual attention to information relevant for classroom management in one of three instructional conditions. Participants viewed two classroom videos and clicked a button whenever they identified situations relevant to classroom management in the videos. They got either (1) a specific task instruction before video viewing (n = 45), (2) attention-guiding prompts during video viewing (n = 45), or (3) a general task instruction (n = 45) before video viewing as a control group. We expected a specific task instruction and prompts to better guide participants’ visual attention compared to a general task instruction before video viewing because both experimental conditions contained informational cues to focus on specific dimensions of classroom management. As both a specific task and prompts were assumed to activate cognitive schemata, resulting in knowledge-based processing of visual information, we expected the specific task instruction to have a similar attention-guiding effect as prompts during video viewing. Measurements were conducted on an outcome level (mouse clicks) and on a process level (eye tracking). Findings confirmed our hypotheses on an outcome level and in part on a process level regarding participants’ gaze relational index. Nevertheless, in a disruptive classroom situation, participants of the prompting condition showed better attentional performance than participants of the other conditions regarding a higher number of fixation and a shorter time to first fixation on disruptive students. Further qualitative analyses revealed that, when observing classroom videos without instructional guidance, pre-service teachers were less likely to identify disruptive situations in the video and more likely to attend to other situations of classroom management concerning the teachers’ action. We discuss advantages of both attention-guiding instructions for pre-service teacher education in terms of the economy of implementation and the salience of situations.

Teachers' Structuring of Culturally Responsive Social Relations and Secondary Students’ Experience of Warm Demand

Students who experience teacher warm demand (i.e., caring and high expectations) are typically more engaged and successful at school. Yet, relative to White students, students of color tend to report more distant relationships with their White teachers. Leveraging data from 179 6th–9th grade Measures of Effective Teaching project classroom videos, we tested whether teachers’ facilitation of culturally responsive social relations was associated with higher warm demand, and whether these social relations moderated associations between race and warm demand. Results showed that teachers’ promotion of culturally responsive social relations was associated with warm demand, and that this was magnified for White teachers in relation to their discipline practices. Findings suggest that taking a culturally responsive approach to facilitating classroom social relations is critical for teachers seeking to improve students’ experiences of warm demand.

Investigating the Equity Imperative in High School Computer Science Curriculum for Latinx Students

ABSTRACT The goal of this qualitative research is to understand equitable teaching practices of computer science classrooms in the Chicago Public Schools through the video analysis specifically for the Latinx students. Data was collected through video recording from 10 different CPS classrooms. The videos were analyzed qualitative to determine the inquiry driven equitable practices. Though the equitable practices were identified based on the classroom video analysis, literature review on equitable practices and core ECS philosophy informed us to recognize and group the themes and their indicators of equity. This research plays a crucial role in terms of informing the current equitable teaching practices based on the videos in ECS classrooms in Chicago, also the research identifies a need to study further cultural references in terms of teaching computer science curriculum. This research has significance for designing professional development for marginalized population in computer science and possibly for other STEM areas.