Session Information
27 SES 07 A, Perspectives on STEAM, Maths and Physics
Paper Session
Contribution
Teachers’ feedback on learning processes and learning outcomes is regarded to be an important factor for primary school students’ mathematical competencies and their performance-related personality development. Feedback is understood as information by significant others (e.g., parents, teachers, peers) with the intention to support students’ learning processes and to clarify discrepancies between actual performances and desired learning goals (Hattie & Timperley, 2007). For example, Hattie (2003) points out that feedback often relates to “aspects of one’s performance or understanding“ and is considered to be “a `consequence´ of performance“ (p. 2). Positive feedback can be perceived as reinforcing and understood as praise (Pintrich & Schunk, 2002), whereas negative feedback is used, if students have not completed a task successfully (Fong et al., 2019).
Following the ‘Student-Feedback Interaction Model’ (Lipnevich & Smith, 2022), teacher feedback on mathematical learning processes and learning outcomes leads to an increase or a decrease of their intrinsic motivation in maths. Conversely, effects of feedback on learning processes on primary school students’ mathematical competencies are mediated by their intrinsic motivation in maths. Primary school students’ perceived positive teacher feedback can therefore increase their intrinsic motivation in maths and thus promote the acquisition of their mathematical competence, whereas negative feedback impairs their intrinsic motivation and thus also the acquisition of their mathematical competences. Intrinsic motivation can thereby be understood as the intention to learn specific skills or to solve learning tasks (e.g., Graham & Weiner, 2012).
In recent studies, the role of teachers’ positive feedback for students’ intrinsic motivation could be shown in various studies (e.g., Burnett & Mandel, 2010). In addition, correlations between children’s perceptions of positive feedback and their learning outcomes could also be proven (e.g., Baliram & Youde, 2018). Furthermore, the importance of students’ intrinsic motivation for their acquired competences was revealed in many studies (e.g., Hattie, 2009). However, research has demonstrated that negative feedback has an impairing effect on students’ academic performances (Kluger & DeNisi, 1996). Thus, negative feedback seems to lead to a lower intrinsic motivation and lower mathematical performances in the classroom. Despite these findings, it is currently unclear whether and to what extent students’ perceptions of teacher feedback (positive/negative) affect their academic competencies, whether intrinsic motivation mediates this relationship, and how the feedback processing mechanisms operate concretely (Lipnevich & Smith, 2022).
Following the ‘Student-Feedback Interaction Model’ (Lipnevich & Smith, 2022) and on the basis of previous highlighted empirical evidence (e.g., Baliram & Youde, 2018; Burnett & Mandel, 2010; Hattie, 2009; Kluger & DeNisi, 1996), we assume that primary school students’ mathematical competences are significantly predicted by their perceived teacher feedback in maths lessons (positive/negative) and by their intrinsic motivation in maths (H1). Furthermore, we expect primary school students’ intrinsic motivation in maths to be significantly explained by their positive and negative teacher feedback in maths lessons (H2). Finally, we make the assumption that the effect of teacher feedback (positive/negative) on students’ mathematical competences is significantly mediated by their intrinsic motivation in maths (H3).
Method
In our study, N=701 third and fourth grade primary school students from North Rhine-Westphalia, Hesse and Lower Saxony in Germany were asked to fill in questionnaires. In detail, 331 girls and 370 boys participated in our study. At the time of the survey, 57% of the children surveyed were in their third grade and 43% were in their fourth grade. They were asked to provide information on their perceived positive and negative teacher feedback in maths lessons and their intrinsic motivation in maths. Furthermore, they also completed a maths test as part of the study. In detail, primary school students’ perceptions of their positive (6 items; e.g., “How often does your teacher say this to you? – Well done!”; α=.85) and negative teacher feedback (6 items; e.g., “How often does your teacher say this to you? – That wasn’t good!“; α=.82) were measured on the basis of two questionnaire scales. We adopted both scales from the work of Burnett (2002). In addition, primary school students were asked to provide information on their intrinsic motivation in maths (5 items; e.g., “I like solving mathematical problems.“; α=.92; Thomas & Müller, 2011). The children made their assessments on 5-point Likert scales (1 = strongly disagree to 5 = strongly agree). Primary school students’ mathematical competencies were assessed by the standardized German mathematical competencies test called DEMAT (“German Mathematics Test”). Students in the third grade completed a maths test for the third school year (DEMAT 3+, Roick et al., 2018) and students in the fourth grade completed a maths test for the fourth school year (DEMAT 4, Görlitz et al., 2006).
Expected Outcomes
For the evaluation of our hypotheses, a structural equation model was calculated to test whether primary school students’ mathematical competencies can be predicted by their perceived positive and negative teacher feedback and their intrinsic motivation in maths lessons. In addition, we modelled primary school students’ perceived positive and negative feedback as exogenous latent variables for their intrinsic motivation in maths. Furthermore, primary school students’ intrinsic motivation in maths was applied to be a mediator between their perceived teacher feedback (positive/negative) and their mathematical competencies. The empirical structural equation model shows a good fit to the theoretical model structure (χ2=296.864; df=158; χ2/df=1.88; RMSEA=.035; CFI=.967; TLI=.961; SRMR=.041). Supporting hypothesis H1, the results of the structural equation model indicate that students’ mathematical competencies can be predicted by their intrinsic motivation and by their perceived negative teacher feedback (R2=.18). However, not supporting hypothesis H1, students’ mathematical competencies cannot be explained by their perceived positive teacher feedback. Supporting hypothesis H2, primary school students’ intrinsic motivation is significantly explained by their perceived positive and negative teacher feedback (R2=.22). Supporting hypothesis H3, the effect of primary school students’ perceived negative feedback on their mathematical competencies is significantly mediated by their intrinsic motivation in math lessons. Contrary to our expectations, the effect of students’ perceived positive feedback on their mathematical competencies is not significantly mediated by their intrinsic motivation. Overall, the results of our study point out correlations between primary school students’ perceived teacher feedback, their intrinsic motivation and their mathematical competencies. Contrary to our expectations, primary school students’ mathematical competencies are not predicted by their perceived positive teacher feedback. In further studies, this unexpected finding needs to be taken into consideration. For this purpose, alternative methodical approaches (e.g., observational studies, qualitative studies) should possibly be applied.
References
Baliram, N. S., & Youde, J. J. (2018). A meta-analytic synthesis: Examining the academic impacts of feedback on student achievement. International Dialogues on Education: Past and Present, 5(2), 76–90. Burnett, P. C. (2002). Teacher praise and feedback and students’ perceptions of the classroom environment. Educational Psychology, 22(1), 5–16. Burnett, P. C., & Mandel, V. (2010). Praise and feedback in the primary classroom: Teachers’ and students’ perspectives. Australian Journal of Educational & Developmental Psychology, 10, 145–154. Eccles, J. S. (2005). Subjective task value and the Eccles et al. model of achievement-related choices. In A. J. Elliot, & C. S. Dweck (Eds.), Handbook of Competence and Motivation (pp. 105–121). Guilford Press. Fong, C. J., Patall, E. A., Vasquez, A. C., & Stautberg, S. (2019). A meta-analysis of negative feedback on intrinsic motivation. Educational Psychology Review, 31(1), 121–162. Graham, S., & Weiner, B. (2012). Motivation: Past, present, and future. In K. R. Harris, S. Graham, & T. Urdan (Eds.), Educational psychology handbook (Vol. 1, pp. 367–397). American Psychological Association. Görlitz, D., Roick, T., & Hasselhorn, M. (2006). DEMAT 4 – Deutscher Mathematiktest für vierte Klassen [DEMAT 4 – German mathematics test for fourth graders]. Hogrefe. Hattie, J. (2003). Why is it so difficult to enhance self-concept in the classroom: The power of feedback in the self-concept-achievement relationship. Paper presented at the International SELF conference, Sydney, Australia. Hattie, J. A. C. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement. Routledge. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284. Lipnevich, A. A., & Smith, J. K. (2022). Student-feedback interaction model: Revised. Studies in Educational Evaluation, 75, 101208. Pintrich, P. R., & Schunk, D. H. (2002). Motivation in education. Theory, research, and applications (2nd ed.). Merrill Prentice Hall. Roick, T., Görlitz, D., & Hasselhorn, M. (2018). DEMAT 3+ – Deutscher Mathematiktest für dritte Klassen [DEMAT 3+ – German mathematics test for third graders]. Beltz. Thomas, A. E., & Müller, F. H. (2011). Skalen zur motivationalen Regulation beim Lernen von Schülerinnen und Schülern. Wissenschaftliche Beiträge aus dem Institut für Unterrichts- und Schulentwicklung [Scales for motivational regulation in student learning. Scientific contributions from the Institute for Teaching and School Development], 5. Alpen-Adria-Universität.
Update Modus of this Database
The current conference programme can be browsed in the conference management system (conftool) and, closer to the conference, in the conference app.
This database will be updated with the conference data after ECER.
Search the ECER Programme
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance, please use the conference app, which will be issued some weeks before the conference and the conference agenda provided in conftool.
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.