Previous studies have extensively explored the direct influence of teacher feedback on students' performance. However, a knowledge gap exists in the question of whether excessively timely, detailed, and accurate feedback might diminish student’s interest in self-learning has not been adequately addressed. Personally, I like and respect the model of quickly accurate feedback (QAF) as a teaching model. Based on that, the research program described in this paper specifically focuses on the micro-level analysis of the self-regulated learning process. This study specifically investigates whether and how quickly accurate feedback can improve students' self-regulated learning processes, which include three parts: meta-cognitive processes, motivational processes, and behavioral processes.

 

 

 

 

It is well-established that teachers frequently provide feedback to students regarding their learning performance, and this feedback mechanism plays a critical role in communication and response, which transfer knowledge, methodology, and education principles. Many researchers have developed multidimensional theories to explore feedback from various perspectives, including form, direction, time, content, relevancy, and general or specific referent (Oliver, 1983; Pieron & Delmelle, 1981; Pieron & Devillers, 1980). Lots of research has investigated teacher feedback interventions, which explore effective feedback and ineffective feedback or negative feedback on learning. Several studies have demonstrated that detailed, positive, and data-based feedback can get more responses from students (Landin et al., 1989; Cusimano, 1987; van der Mars, 1987). Conversely, other studies have found no significant relationship between the amount of teachers’ feedback and students’ final performance (Eghan, 1988; Silverman et al., 1992) and in some cases, even identified a negative influence (Kluger & DeNisi, 1996). Ultimately, it is the student who determines the perceived efficacy of the feedback (Carvalho et al., 2014; Hattie, 2003).

 

 

According to Zimmerman (1986) and Zimmerman & Schunk (1989), “students are self-regulated to the degree that they are meta-cognitively, motivationally, and behaviorally active participants in their own learning process." Self-regulated learning encompasses three key areas. First, the meta-cognitive processes, which involve planning and goal setting, organizing, self-monitoring, and self-evaluating. Second is the motivational processes, including high self-efficacy, self-attributions, and intrinsic task interest. Third, behavioral processes, include selecting, structuring, and creating environments that optimize learning. As introduced, a self-regulated learner does well in acquiring and generating knowledge by delaying gratification, maintaining a strong academic identity, attentively monitoring feedback from their own work, setting goals, and holding high expectations for their own performance in different situations and tasks. They stay focused and pay attention even when there are distractions; and they master academic challenges through self-articulation, co-construction, and the selection of appropriate goals and strategies. It’s quite a perfect setting for a learner (Ainley & Patrick, 2006).

 

 

 

 

This study focuses on the micro-level investigation of the self-regulated learning process, specifically examining the impact of timely and accurate feedback on students’ self-regulated learning. The study is structured around three core components of self-regulated learning: metacognitive processes, motivational processes, and behavioral processes.

 

 

The Student Research Engagement and Development (S-RED) Programme was initiated by the XIPU Institution for XJTLU students. Under the supervision of the principal investigator, students will be able to gain a good understanding of a range of research methods and obtain first-hand experience in conducting research projects.

 

During the first semester of the 2023-2024 academic year, I hosted a social science research project focused on the ESG (Environmental, Social, and Governance) ranking performance of Suzhou-listed firms and strategies for its enhancement. The project team consists of five XJTLU postgraduates who major in fintech, with myself serving as the PI. We meet once a week and work together to produce a policy report as the research outcome.

 

 

 

I provide prompt timely, and accurate feedback on students’ weekly progress. After their presentations of recent work, I directly communicated what they had done well and where improvements were needed, with a kindly attitude and a very detailed introduction. My feedback includes suggestions on how to address the deficiencies and bridge research gaps, including the accurate information channel, the effective searching method, the data standardized treatment, the data analysis method, and even the color of graphs and figures [A3; A4; A5; V3; V4]. While I anticipate that my feedback will have an immediate positive impact on students, the ultimate effect will be revealed through the survey data.

 

 

First, I designed a survey to assess students’ levels of self-regulated learning every two weeks and a total of four questionnaires. The survey comprises 10 questions covering three areas of self-regulation (as Appendix I shows). These 10 key factors include planning and goal setting, organizing, self-monitoring, self-evaluate, self-efficacy, self-attributions, intrinsic task interest, and selecting, structuring, and creating environments that optimize learning [A4; A5; K3; K5; V4]. Second, throughout the project, I conducted face-to-face and one-on-one conversations with each student to understand their perspectives on this project and my feedback, how they integrated my advice, and whether they developed self-regulated learning abilities [K3; K5; V4]. Third, at the end of the project, five students were asked to complete another questionnaire to determine if the teacher’s QAF influences the nine key factors of the students’ self-regulated learning process and how the influence appears [A4; A5; K3; K5; V4].

 

 

 

 

Figures 1, 2, and 3 show how the five students (X, Y, Z, L, and F) self-assess their self-regulated learning over a period of three months.

 

 

 

Fig. 1 presents the change in meta-cognitive processes, which are assessed through four questions outlined in Appendix I. The results indicate that two of the five students exhibited an increase in their meta-cognitive profile, while one student experienced a decrease.

 

 

 

Fig. 2 depicts the changes in motivational processes, evaluated by three questions, as shown in Appendix I. The findings reveal that one of the five students demonstrated an improvement in her motivational profile, whereas three students showed a decline in their motivational profile.

 

 

 

Fig. 3 illustrates the changes in behavioral processes, assessed through three questions, as described in Appendix I. As a result, two of the five students showed an increase in their behavioral profile, while three students experienced a decrease in their motivational profile.

 

For the weekly questionnaire results presented in the three figures, there are three reasons to explain the fact that some students' self-regulated learning has decreased instead. Firstly, from the raw data of the questionnaire, it can be found that most of the students provided more negative responses in the final questionnaire. This questionnaire was administered in late November, a period marked by increased project difficulty and the later stages of the project, which is likely to contribute to a lower self-evaluation among students. Secondly, in my interviews with students, they mentioned that the distinctions between response options in the questionnaire were not significant to them. For example, they did not perceive a meaningful difference between "well" and "very well," and so they often chose one at random. This, however, resulted in a drop in marks. Thirdly, students are influenced by QAF. In terms of the question “How often do you create a plan before starting a learning task?" some students said, "Because Prof. Wang helped us plan all our study tasks, I don't want to plan anymore myself". The “Prof. Wang” mentioned in this context refers to me.

 

 

First, here are excerpts from five students' overall opinions on the teacher’s QAF model used in this research project:

 

• "I think Prof. Wang's QAF teaching mode is very good. By dividing up the work and letting us research on our own first, after which the teacher gives timely feedback, it is conducive to the improvement of my scientific research ability. It also broadens the depth and breadth of my thinking." (Student X, Dec 2023)

 

• "I personally prefer the QAF teaching mode to the teacher's step-by-step guidance. Timely feedback from the teacher not only solves one's own doubts but also saves the team time. However, in my understanding and perception, I believe that such a teaching model requires a lot of knowledge and practical experience from the teacher in order to be able to react quickly to the questions, and therefore the answers given by the teacher are to a certain extent subjective. In our ESG research program, subjective questions were rarely involved, so we were not able to detect this problem. If some subjective issues are involved in the discussion, the students' and teachers' views may differ. And I am a person who easily trusts authority, and in extreme cases, even if what the teacher expresses deviates from the facts, I will convince myself to think according to the teacher's method." (Student Y, Dec 2023)

 

• "The QAF teaching model has significantly helped my learning and research skills while providing efficient feedback. Timely feedback allowed me to quickly understand my level of understanding and problems, which helped me adjust my learning strategies in a timely manner. At each meeting, Prof. Wang could quickly point out potential problems in the project, prompting the team to adjust before the next meeting. This is critical to keeping the project moving and productive." (Student Z, Dec 2023)

 

• "Personally, I find the QAF teaching method valuable and practical in providing me with timely feedback so that I can quickly understand where they are going wrong and make improvements to increase efficiency. At the same time, this teaching method is really beneficial to the growth of my research skills, and the timely and accurate feedback helps me to organize and understand my knowledge and work content so that I can develop independent thinking and problem-solving skills." (Student L, Dec 2023)

 

• "This teaching model has allowed me to grow a lot and fill in my own gaps in academia, and Prof. Wang has helped me to go and quickly master the skills and methods of academic research. … Overall, I recognize the use of this teaching model in research projects. However, regarding the teaching model itself, QAF is not applicable to all cases, and some studies or topics require students to explore and discover on their own in order to stimulate their creativity. The implementation should be adapted to the different attributes of the research project. For example, for shorter projects, teachers can directly teach students the necessary methods and skills; for longer projects, teachers can encourage students to solve problems on their own in order to stimulate students' self-reflection and summarization skills." (Student F, Dec 2023)

 

From the above text: All five students held positive and affirmative attitudes about the contribution of the QAF teaching model to the program and the development of their academic skills. They identified the advantages of the QAF teaching model as the rapid learning of skills, timely correction of errors, and efficient use of time. Two of the students engaged in deeper reflection on the QAF model. One student thought that the quality of the QAF mode depended on the competence and ability of the teacher and that the QAF mode could over-amplify teachers’ subjective influence on students. Another student proposed that QAF mode was more suitable for short-term courses, while longer-term courses should focus more on students' exploration and creativity.

 

Table 1 demonstrates the impact of the QAF model on students' self-regulated learning processes. The question of this questionnaire is, "Does the teacher’s quickly accurate feedback model influence you in any of the following areas? If yes, how does it influence?”.

 

 

 

 

 

 

The study concludes that the QAF teaching model improves students' self-regulated learning processes, particularly in metacognitive and motivational aspects. However, the results were not statistically significant. While Students generally acknowledged the role and efficiency of the QAF, they also suggested that the QAF does not apply to all courses and projects and should be adapted locally.

 

This study has several limitations, the greatest of which is the sample limitation, both in terms of the number of participants and the duration of the observation. Given these limitations, the study serves as a preliminary and insufficient exploration of the topic. I look forward to the future with better quasi-experimental opportunities and larger student samples to answer the core question, “Can Providing Quickly Accurate Feedback Improve Students' Self-Regulated Learning Processes?”.

 

APPENDIX I: Weekly Questionnaire of Students’ Self-Regulated Learning

 

 

APPENDIX II: Final Questionnaire of Teacher’s Quickly Accurate Feedback

 

 

 

 

 

 

Ainley, M., & Patrick, L. (2006). Measuring self-regulated learning processes through tracking patterns of student interaction with achievement activities. Educational Psychology Review, 18, 267-286.

 

Carvalho, C., Santos, J., Conboy, J., & Martins, D. (2014). Teachers’ feedback: Exploring differences in students’ perceptions. Procedia-Social and Behavioral Sciences, 159, 169-173.

 

Cusimano, B. E. (1987). Effects of self-assessment and goal setting on verbal behavior of elementary physical education teachers. Journal of Teaching in Physical Education, 6(2), 166-173.

 

Eghan, T. (1988). The relation of teacher feedback to student achievement in learning selected tennis skills. Louisiana State University and Agricultural & Mechanical College.

 

Hattie, J. (2003). Teachers make a difference: what is the research evidence? Camberwell: Australian Council for Educational Research.

 

Higher Education Academy. (2011). The UK Professional Standards Framework for teaching and supporting learning in higher education.

 

Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: Historical review, a meta-analysis and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254-284.

 

Landin, D. K., Hebert, E., & Cutton, D. (1989). Analyzing the augmented feedback patterns of professional tennis instructors. Journal of Applied Research in Coaching and Athletics, 4(25), 5-271.

 

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Phillips, D. A., & Carlisle, C. (1983). A comparison of physical education teachers categorized as most and least effective. Journal of teaching in physical education, 2(3), 55-67.

 

Pieron, M., & Delmelle, R. (1981). Descriptive study of teacher's feedback in two educational situations. Artus, 9(11), 193-196.

 

Piéron, M., & Devillers, C. (2013, December). Multi-dimensional analysis of informative feedback in teaching physical activities. In Audiovisuelle Medien in Sport.

Silverman, S., Tyson, L., & Krampitz, J. (1992). Teacher feedback and achievement in physical education: Interaction with student practice. Teaching and teacher education, 8(4), 333-344.

 

Van der Mars, H. (1987). Effects of audiocueing on teacher verbal praise of students’ managerial and transitional task performance. Journal of Teaching in Physical Education, 6(2), 157-165.

 

Zimmerman, B. J. (1986). Development of self-regulated learning: Which are the key subprocesses? Contemporary Educational Psychology, 16, 307–313.

 

Zimmerman, B. J., & Schunk, D. H. (1989). Self-regulated learning and academic achievement: Theory, research and practice. Berlin Heidelberg New York: Springer.