Teacher Feedback Research Articles

Fostering self-regulated learning-focused feedback: Getting preservice teachers prepared

Since self-regulated learning (SRL) has been integrated into educational objectives, it is crucial for EFL teachers to incorporate SRL elements, such as feedback, into their instructional practices. Given the inherent complexity of the feedback process and the challenges associated with changing in-service teachers' feedback focus, developing preservice teachers’ literacy at the beginning of their professional careers is essential. To investigate the extent to which preservice teachers can generate multifocus feedback incorporating an SRL element, this study analyses the feedback categories generated by 286 preservice teachers and examines the underlying factors that influence their feedback choices using a mixed-methods approach. The feedback pattern analysis revealed that, despite recognizing the importance of SRL, preservice teachers struggled with creating multiple feedback entries supporting SRL. An investigation into SRL-focused feedback patterns and their influencing factors suggested several ways to embed SRL into the core of teacher feedback. These include building teacher beliefs to cultivate collegial resources, constructing a databank of feedback comments on SRL activities to facilitate feedback provision, and examining learner differences to craft individualized feedback. The conclusion summarizes the implications for future feedback studies, outlining an agenda for further research in this area.

A multimodal approach to support teacher, researcher and AI collaboration in STEM+C learning environments

AbstractRecent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open‐ended environments. AI systems are known to underperform humans in (1) interpreting students' emotions in learning contexts, (2) grasping the nuances of social interactions and (3) understanding domain‐specific information that was not well‐represented in the training data. As such, combined human and AI (ie, hybrid) approaches are needed to overcome the current limitations of AI systems. In this paper, we take a first step towards investigating how a human‐AI collaboration between teachers and researchers using an AI‐generated multimodal timeline can guide and support teachers' feedback while addressing students' STEM+C difficulties as they work collaboratively to build computational models and solve problems. In doing so, we present a framework characterizing the human component of our human‐AI partnership as a collaboration between teachers and researchers. To evaluate our approach, we present our timeline to a high school teacher and discuss the key insights gleaned from our discussions. Our case study analysis reveals the effectiveness of an iterative approach to using human‐AI collaboration to address students' STEM+C challenges: the teacher can use the AI‐generated timeline to guide formative feedback for students, and the researchers can leverage the teacher's feedback to help improve the multimodal timeline. Additionally, we characterize our findings with respect to two events of interest to the teacher: (1) when the students cross a difficulty threshold, and (2) the point of intervention, that is, when the teacher (or system) should intervene to provide effective feedback. It is important to note that the teacher explained that there should be a lag between (1) and (2) to give students a chance to resolve their own difficulties. Typically, such a lag is not implemented in computer‐based learning environments that provide feedback. Practitioner notesWhat is already known about this topic Collaborative, open‐ended learning environments enhance students' STEM+C conceptual understanding and practice, but they introduce additional complexities when students learn concepts spanning multiple domains. Recent advances in generative AI and MMLA allow for integrating multiple datastreams to derive holistic views of students' states, which can support more informed feedback mechanisms to address students' difficulties in complex STEM+C environments. Hybrid human‐AI approaches can help address collaborating students' STEM+C difficulties by combining the domain knowledge, emotional intelligence and social awareness of human experts with the general knowledge and efficiency of AI. What this paper adds We extend a previous human‐AI collaboration framework using a hybrid intelligence approach to characterize the human component of the partnership as a researcher‐teacher partnership and present our approach as a teacher‐researcher‐AI collaboration. We adapt an AI‐generated multimodal timeline to actualize our human‐AI collaboration by pairing the timeline with videos of students encountering difficulties, engaging in active discussions with a high school teacher while watching the videos to discern the timeline's utility in the classroom. From our discussions with the teacher, we define two types of inflection points to address students' STEM+C difficulties—the difficulty threshold and the intervention point—and discuss how the feedback latency interval separating them can inform educator interventions. We discuss two ways in which our teacher‐researcher‐AI collaboration can help teachers support students encountering STEM+C difficulties: (1) teachers using the multimodal timeline to guide feedback for students, and (2) researchers using teachers' input to iteratively refine the multimodal timeline. Implications for practice and/or policy Our case study suggests that timeline gaps (ie, disengaged behaviour identified by off‐screen students, pauses in discourse and lulls in environment actions) are particularly important for identifying inflection points and formulating formative feedback. Human‐AI collaboration exists on a dynamic spectrum and requires varying degrees of human control and AI automation depending on the context of the learning task and students' work in the environment. Our analysis of this human‐AI collaboration using a multimodal timeline can be extended in the future to support students and teachers in additional ways, for example, designing pedagogical agents that interact directly with students, developing intervention and reflection tools for teachers, helping teachers craft daily lesson plans and aiding teachers and administrators in designing curricula.

Exploring dynamics of student course feedback in higher education

This article delves into student course feedback using publicly available data from the University of North Texas. It examines factors influencing elevated student course evaluation ratings in the Information Technology and Decision Sciences department. The study reveals a positive relationship between higher response rates and better evaluation scores. The challenge index, individual course engagement, and difficulty are linked to higher scores. Course level impacts scores, with higher-level courses receiving higher ratings. This prompts further investigation into why full professors may not outperform associates in student ratings, advocating for broader research into characteristics influencing course evaluation performance. The study contributes valuable insights into academia and fostering discussions on business faculty assessment.

DEVELOPMENT OF LEARNING MEDIA ON THE MATERIAL OF PRACTICING PANCASILA VALUES IN THE FORM OF A SCRAPBOOK FOR FOURTH GRADE STUDENTS AT SD NEGERI 101961 TIMBANG DELI FOR THE 2023/2024 ACADEMIC YEAR

This research aims to: (1) Determine the development of learning media on the material of practicing Pancasila values in the form of a scrapbook for fourth-grade students, and (2) Assess the feasibility of the learning media developed on the same material. This study employs a Research and Development (R&D) methodology. The subjects of the research are 25 fourth-grade students from SD Negeri 101961 Timbang Deli, consisting of 11 boys and 14 girls. According to the material experts' assessment, the feasibility percentage is 94%, categorized as "Highly Feasible." The media experts' assessment shows a feasibility percentage of 96%, also categorized as "Highly Feasible." Student responses from the trials indicate a feasibility percentage of 91.04%, classified as "Highly Feasible." Similarly, based on teacher feedback, the feasibility percentage is 90.7%, with the same classification of "Highly Feasible." The media has been validated by both media and material experts, and it is deemed highly suitable for use as a learning tool for the material on practicing Pancasila values in the form of a scrapbook for fourth-grade students at SD Negeri 101961 Timbang Deli.

The Effect of Teacher’s Feedback on Student Academic Achievement: A Literature Review

The role of teacher’s feedback in the teaching and learning process is extremely important as it allows educators to provide an objective assessment of a student’s performance and help them improve their academic achievements. In this paper, the findings of a comprehensive literature review, conducted using the PRISMA methodology, encompassing 19 studies from 2013 to 2023 are presented. These studies evaluated the impact of teacher feedback on students’ academic performance across all levels of education. It was observed that the majority of the research focused on English as a second and foreign language, academic writing, and higher education. The data collection method employed in these studies was action research. The results indicated that the provision of various forms of teacher’s feedback significantly contributed to enhancing students’ academic performance, improving their language skills, and refining their academic writing abilities.

Application of high-performance computing in sustainable energy campus building design

In high-performance computing (HPC) systems, energy and power considerations play an increasingly important role. This work aims to ensure the implementation of China’s green and ecological concepts, respond to China’s strategy of building an environment-friendly and resource-saving society, and actively promote the construction of sustainable development campuses. First, the theoretical basis of sustainable energy campus architecture is described. Next, the teaching feedback model under HPC is constructed. Finally, with the evaluation results of students’ task completion processes and students’ task works as measurement indexes, the corresponding data is collected and comprehensively evaluated and analyzed to verify the effectiveness of the model. The analysis results indicate that most students are able to complete tasks within two hours; however, their proficiency with multimedia technology is inadequate, and they lack initiative in the learning process. There is a correlation between the overall evaluation of task performance and the students’ level of understanding of the tasks. By implementing a teaching feedback model, students’ learning enthusiasm and the quality of their work improved, providing effective educational support for promoting sustainable development on campus. Overall, the awareness of using computers and other multimedia technologies among students is not strong, and their learning process is relatively closed, with insufficient enthusiasm and initiative. This model can achieve the acquisition, integration, and statistical analysis of teacher feedback information. The model can realize the acquisition, integration, and statistical analysis of teachers’ feedback information. This work hopes to use this learning and feedback mode in practical teaching to address specific problems in computer multimedia courses.

Revisiting writing feedback: Using teacher-student writing conferences to enhance learners’ L2 writing skills

Previous studies have largely overlooked teacher feedback, which plays a significant role in the social construction of knowledge within educational ecosystems worldwide. While written corrective feedback has been the focus of writing feedback research, oral feedback in teacher-student L2 writing conferences has not received as much attention, especially from an ecological lens. To address this research gap, this study investigated how writing training, including teacher-student conferences, can improve learners' L2 writing skills, with a specific focus on Ethiopia. The study explores how these conferences can help students enhance their L2 writing skills through constructive criticism and encouragement. To achieve this, 63 students (aged 15 to 23; 38 male and 25 female) were divided into experimental and control groups using a quasi-experimental design. The students underwent pre- and post-tests during an eight-week intervention. MANOVA was used to evaluate the pre-test data, while ANCOVA was used for the post-test analysis. The post-test results show that teacher-student conferences can effectively improve three writing skills: organization, vocabulary, and mechanics. The greatest impact on students' understanding of the writing process was seen in mechanics (43.4%), vocabulary (36.9%), and organization (11.5%). However, the intervention did not have a statistically significant impact on two other writing skills: content and language usage or grammar. Recommendations for future research and strategies for integrating teacher-student conferences into writing instruction are provided.

The analysis of art design under improved convolutional neural network based on the Internet of Things technology

This work aims to explore the application of an improved convolutional neural network (CNN) combined with Internet of Things (IoT) technology in art design education and teaching. The development of IoT technology has created new opportunities for art design education, while deep learning and improved CNN models can provide more accurate and effective tools for image processing and analysis. In order to enhance the effectiveness of art design teaching and students’ creative expression, this work proposes an improved CNN model. In model construction, it increases the number of convolutional layers and neurons, and incorporates the batch normalization layer and dropout layer to enhance feature extraction capabilities and reduce overfitting. Besides, this work creates an experimental environment using IoT technology, capturing art image samples and environmental data using cameras, sensors, and other devices. In the model application phase, image samples undergo preprocessing and are input into the CNN for feature extraction. Sensor data are concatenated with image feature vectors and input into the fully connected layers to comprehensively understand the artwork. Finally, this work trains the model using techniques such as cross-entropy loss functions and L2 regularization and adjusts hyperparameters to optimize model performance. The results indicate that the improved CNN model can effectively acquire art sample data and student creative expression data, providing accurate and timely feedback and guidance for art design education and teaching, with promising applications. This work offers new insights and methods for the development of art design education.

Feedback in higher education in Asian countries: an approach

Feedback in higher education in Asian countries: an approach

Enhancing High School Mathematics Education Through School-based Research: Development and Mechanisms

In the context of ongoing educational reforms aimed at fostering critical competencies among high school students, this paper explores the implementation and impact of school-based mathematics research (SBR) as a strategic innovation within the high school curriculum. Adopting mixed research methods, in the study questionnaires were distributed to all students and teachers in the early stage to collect and analyze relevant data and than the study combines quantitative analyses of student performance data with qualitative insights from teacher and student feedback to assess the effects of SBR on teaching practices and learning outcomes. This research is based on the fact that the traditional education model cannot meet the needs of cultivating students' thinking ability, and the new curriculum reform has decentralized teaching research to schools. The study is helpful to explore the effect of SBR on the cultivation of teachers' scientific research ability and the improvement of classroom quality. The results show the powerful role of SBR in promoting teaching practice and student participation. Based on school characteristics, it proposes effective teaching improvement measures to improve the quality of mathematics education.

Enhancing writing ability of Iranian EFL learners through learning-oriented assessment: peer and teacher feedback implementation

Despite the widespread use of Learner-Oriented Assessment (LOA) in (English as a Foreign Language EFL classes, concerns persist regarding its suitability for contexts such as Iran. Drawing on Carless’s (SHE, 31:219-233, 2006) criteria for LOA, the present study examined the effectiveness of peer and teacher feedback in an academic writing course. To this aim, a total of 124 intermediate language learners who were homogenized in terms of language proficiency, based on the Common European Framework of Reference for Languages (CEFR), were randomly assigned to an experimental and a control group. A 12-session writing instruction course with specific writing tasks was developed. One group received feedback from peers, while the other group received feedback from the teacher. Findings revealed that peer feedback resulted in better writing in terms of language, content, and organization. It was also found that the peer feedback group could retain their learning in the long run. These findings underscore the effectiveness of peer feedback within the framework of LOA, particularly in teacher-directed settings.

Comparative Study About the Impacts of Chinese Automated Writing Evaluation (AWE) Feedback and Teacher Feedback on Middle School Students’ Writing Practice

Comparative Study About the Impacts of Chinese Automated Writing Evaluation (AWE) Feedback and Teacher Feedback on Middle School Students’ Writing Practice

EXPLORING STUDENT ENGAGEMENT WITH FORMATIVE ASSESSMENT AND ICT TOOLS

This study investigates the potential of Information and Communication Technology (ICT) tools to enhance formative assessment (FA) practices in English as a Foreign Language (EFL) classrooms. While previous research has focused primarily on teacher feedback in writing courses, this study emphasizes a broader scope of FA. Utilizing a cross-sectional, quantitative analysis, the research examines how ICT tools support FA's goal of facilitating the learning process from students' perspectives, thereby informing effective teaching practices and improving learning outcomes. Participants included 173 university EFL students in Japan, divided into English majors and non-English majors. The study employed a revision of an existing survey for language learning with digital tools and a self-developed survey based on an existing framework for FA. Correlational analysis indicated that participants generally perceived ICT tools as supportive of all five FA principles. Despite issues like connectivity problems, students found the tools valuable for making the learning progress visible and enhancing peer communication. The study underscores the importance of understanding and practicing FA beyond feedback, such as clarifying learning goals and fostering peer learning, to enhance learning. These findings suggest that integrating ICT tools into FA practices can significantly benefit EFL instruction by promoting student engagement and self-regulated learning.

Harnessing Generative AI (GenAI) for Automated Feedback in Higher Education: A Systematic Review

In this systematic review, we synthesize ten empirical peer-reviewed articles published between 2019 and 2023 that used generative artificial intelligence (GenAI) for automated feedback in higher education. There are significant opportunities and challenges to integrate these tools effectively into learning environments as the demand for timely and personalized feedback grows. We examine the articles based on instructional contexts and system characteristics, identifying critical implementation possibilities for GenAI in automated feedback. Our findings reveal that GenAI provides diverse feedback across various contexts with multiple instructional purposes. GenAI systems can reduce instructor workload by automating routine grading and feedback tasks, allowing educators to focus on more complex teaching responsibilities with augmented capabilities. Additionally, these systems enhance communication, offer cognitive and emotional support, and improve accessibility by creating supportive, stress-free learning environments. Overall, implementing GenAI automated feedback systems improves educational outcomes and creates a more efficient and supportive learning environment for students and instructors. We conclude with future research directions to better integrate GenAI with human instruction by reconsidering instructors’ roles, especially in providing feedback to create more effective educational experiences.

International Students’ Perspectives on the Use of Summative Feedback in UK Higher Education

Feedback is a crucial element in higher education, essential for academic improvement. It can come from various sources such as teachers, peers, and personal experiences. The main goal of feedback is to correct mistakes, close gaps, and enhance knowledge and skills. The study focuses on international students at UK universities, identifying several factors that hinder their engagement with summative feedback. These include the timing of feedback release, often coinciding with exams or holidays, and the lack of detail in feedback content. The study suggests adjusting the timing and tone of feedback to make it more effective and encouraging.

The Effects and EFL College Students’ Perceptions on Online-based Teacher Feedback, Peer Feedback, and Self-feedback in Writing Classes: Focusing on Comparison of Level-differentiated Learners

The Effects and EFL College Students’ Perceptions on Online-based Teacher Feedback, Peer Feedback, and Self-feedback in Writing Classes: Focusing on Comparison of Level-differentiated Learners

Optimizing Soldier Counseling: Multi-Source, Mixed-Method Evaluation of a Developmental Counseling Training for Mid-Grade Level Leaders.

In accordance with ADP 6-22-001 and ATP 6-22.1, counseling is the process routinely executed by Army leaders to develop, mentor, and coach subordinate Soldiers and Army civilians within their organization. When implemented effectively, the counseling process can be utilized to produce capable, resilient, and satisfied subordinates who are prepared and motivated to meet mission-essential responsibilities. Training opportunities that specifically focus on optimizing this key leader competence, particularly with non-commissioned officers, are limited. The Directorate of Prevention, Resilience and Readiness (Headquarters, Department of the Army, G-9) offers a specific training, the Counseling Enhancement Workshop, and requested an evaluation to determine the effectiveness of the current training and identify opportunities for improvement. A longitudinal 360-degree approach was deployed as a common multisource methodology intended to produce triangulated feedback from participants, as well as their subordinates and supervisors. Quantitative surveys and qualitative structured interviews were conducted. Performance psychology professional facilitators who train this workshop were also administered a questionnaire to capture instructional feedback. Measures include a knowledge assessment of the workshop content, Counseling Self-Efficacy Survey, as well as original measures related to the workshop experience. Completed written developmental counseling forms and observations from the evaluation team were also reviewed to ensure fidelity of the training implementation and delivery. The current study reports on survey responses from participants and facilitators. Results suggested a strong and positive correlation between the pre- and post-workshop Counseling Self-Efficacy Scale. Because of a small sample size, data were analyzed as planned but interpreted with caution because of limited validity. There was a significant increase between the pre- and post-tests knowledge comprehension test scores. Facilitators reported confidence in teaching resilience skills, but not coaching Soldiers to apply those skills as part of the developmental counseling process. The Army counseling process can be utilized to produce capable, resilient, and satisfied subordinates who are prepared and motivated to meet mission-essential responsibilities. Quantitative results on the content of the CEW present opportunities for meaningful training that increases leaders' confidence in delivering counseling sessions, as well as mastering specific skills that benefit the subordinate Soldier and improve unit health. Furthermore, performance psychology professionals provided feedback on focus areas to meet the instructional objective of the training more efficiently and effectively. Ultimately, the counseling process is considered the most important tool available to current leaders to build the capacity of future leaders and an investment in the training to enhance these skills will provide great returns to the U.S. Army as a whole.

More, better feedback please: are learning analytics dashboards (LAD) the solution to a wicked problem?

There is a long-standing lack of learner satisfaction with quality and quantity of feedback in health professions education (HPE) and training. To address this, university and training programmes are increasingly using technological advancements and data analytic tools to provide feedback. One such educational technology is the Learning Analytic Dashboard (LAD), which holds the promise of a comprehensive view of student performance via partial or fully automated feedback delivered to learners in real time. The possibility of displaying performance data visually, on a single platform, so users can access and process feedback efficiently and constantly, and use this to improve their performance, is very attractive to users, educators and institutions. However, the mainstream literature tends to take an atheoretical and instrumentalist view of LADs, a view that uncritically celebrates the promise of LAD's capacity to provide a 'technical fix' to the 'wicked problem' of feedback in health professions education. This paper seeks to recast the discussion of LADs as something other than a benign material technology using the lenses of Miller and Rose's technologies of government and Barry's theory of Technological Societies, where such technical devices are also inherently agentic and political. An examination of the purpose, design and deployment of LADs from these theoretical perspectives can reveal how these educational devices shape and govern the HPE learner body in different ways, which in turn, may produce a myriad of unintended- and ironic- effects on the feedback process. In this Reflections article we wish to encourage health professions education scholars to examine the practices and consequences thereof of the ever-expanding use of LADs more deeply and with a sense of urgency.

Teacher- Versus AI-Generated (Poe Application) Corrective Feedback and Language Learners’ Writing Anxiety, Complexity, Fluency, and Accuracy

This study examines the effects of corrective feedback (CF) on language learners’ writing anxiety, writing complexity, fluency, and accuracy, and compares the effectiveness of feedback from human teachers with an AI-driven application called Poe. The study included three intact classes, each with 25 language learners. Using a quasi-experimental design with pretest and posttest measures, one class received feedback from the teacher, one from the Poe application, and the third received no response to their writing. Data were generated though tests and a writing anxiety scale developed for the study. Data analysis, conducted using one-way ANOVA tests, revealed significant effects of teacher and AI-generated feedback on learners’ writing anxiety, accuracy, and fluency. Interestingly, the group that received AI-generated feedback performed better than the group that received teacher feedback or no AI support. Additionally, learners in the AI-generated feedback group experienced a more significant reduction in writing anxiety than their peers. These results highlight the remarkable impact of AI-generated CF on improving writing outcomes and alleviating anxiety in undergraduate language learners at East China University of Political Science and Law . The study demonstrates the benefits of integrating AI applications into language learning contexts, particularly by promoting a supportive environment for students to develop writing skills. Educators, researchers, and developers can use these findings to inform pedagogical practices and technological interventions to optimize the language learning experience in primary school settings. This research highlights the effectiveness of AI-driven applications in language teaching. It highlights the importance of considering learners’ psychological well-being, particularly anxiety levels, when developing effective language learning interventions.

Orchestrating Teacher, Peer, and Self-Feedback to Enhance Learners’ Cognitive, Behavioral, and Emotional Engagement and Public Speaking Competence

Previous research on providing feedback on public speaking has investigated the effectiveness of feedback sources, namely teacher feedback, peer feedback, and self-feedback, in enhancing public speaking competence, predominantly individually. However, how these sources of feedback can be collectively harnessed to optimize learner engagement and public speaking performance still warrants further investigation. Adopting a pre- and post-test quasi-experimental design, this study randomly assigned four classes to four feedback conditions: Group 1 received teacher feedback, Group 2 self-feedback and teacher feedback, Group 3 peer and teacher feedback, and Group 4 feedback from all three sources. Both student engagement, measured using the Public Speaking Feedback Engagement Scale (PSFES), and their public speaking performance ratings, assessed using the Public Speaking Competency Instrument (PSCI), were validated using Rasch analysis. The inferential statistics revealed that Group 3 showed significant improvements across nearly all three dimensions of engagement, whereas Group 2 experienced significant declines in all dimensions of engagement except behavioral engagement. Group 3 demonstrated significantly greater engagement gain compared to Groups 2 and 4, indicating the synergistic effect of peer and teacher feedback in contrast to the limited impact of self-feedback. Additionally, all groups demonstrated significant improvements except for Group 2, which showed significantly lower improvement compared to Group 4. The following correlation analysis identified a significant correlation between the gain of students’ behavioral engagement and the gain of public speaking performance, whereas such association was absent between cognitive or emotional engagement and public speaking competence. This study suggests that peer feedback should be preceded by group discussion and supplemented with teacher feedback in classes for enhancing the teacher–student dialog, while self-feedback should be conducted after class to improve student engagement and public speaking performance.