Feedback - a central component of formative assessment - has been identified to be a powerful tool to influence the learning process (Wisniewski et al., 2019). Feedback is defined as a mean “to reduce discrepancies between current understandings and performance and a goal” (Hattie & Timperley, 2007, p. 86). In contrast to simple feedback, elaborative feedback answers the following questions: Where am I going? (feed up), How am I going? (feed back), Where to next? (feed forward) (Hattie & Timperley, 2007). Studies have pointed out that such an elaborative feedback is superior in effectiveness to less elaborative types of feedback (e.g. only offering knowledge of response or knowledge of result) (van der Kleij et al., 2012). Moreover, students generally perceive elaborative feedback to be more useful (Barry, 2008). However, despite this knowledge, students receive written feedback mostly in the form of simple grades (Lipnevich & Smith, 2009).

It can be assumed that the aforementioned fact is related to the high (work-)load of teachers. Fortunately, there exist teaching-learning platforms that can support students in their learning process and help teachers to reduce their workload. Benefits like this have the potential to drive the digitization of schools – but: While there exist many studies investigating the effectiveness of digital media in schools (as well as in mathematics classrooms), the reported effect sizes vary widely in most of the cases (e.g. Cheung & Slavin, 2013). Additionally, also the new challenges posed by the current pandemic situation make it necessary to investigate and understand how learning can best be supported by digital media and whether results from “traditional” teaching-learning research can be replicated and transferred to the new learning settings.

Both, based on general considerations about the effectiveness of elaborative feedback as well as the open question about how to implement digital media in school effectively, the present study focuses on students practicing with a teaching-learning platform that automatically generates different kinds of feedback for students. Starting from in advance defined criteria, the mathematics specific teaching-learning platform bettermarks was selected as an exemplary platform. The platform can be used both in the web browser and as an application and is available in English, Spanish, Dutch and German. Various studies have already been conducted on the bettermarks learning system and a positive effect on learning effectiveness as well as superiority over other learning platforms has been identified (e.g. Scharnagl et al., 2014; Stein, 2015).

As the previous discussion shows, there is an empirical data base on feedback and student performance and the impact of digital media. However, the results on the influence of digital media on mathematical performance do not provide a consistent picture. Moreover, it has long been assumed that students perceive feedback as it is intended. The students' point of view was therefore neglected for a long time (Strijbos et al., 2010). These problems directly imply to the following desiderata of this study: (1) investigating the effect of the feedback (offered by the teaching-learning platform) on learning outcomes, and (2) analysing students' usage and perceptions of the offered feedback and its influence on learning.

In detail, the following research questions arise:

Question 1: Which impact does the usage of a teaching-learning platform have on students’ mathematics learning?

Question 2: How do students use and perceive the (elaborated) feedback provided by the teaching-learning platform?

Question 3: Do usage and perception of (elaborated) feedback provided by the teaching-learning platform mediate potential effects on students’ mathematics learning?

The study is scheduled to be conducted in mid-2021 and is designed as an experimental laboratory study including mixed-methods. A pre-study is used to parallelize the participating eighth graders according to gender, mathematical compe-tence, reading competence, and cognitive abilities. Afterwards, the students are randomly assigned to an experimental or a control group. Both groups will work with the selected learning platform bettermarks using tablets. Design. During the intervention, the two groups differ in the type of feedback they receive. Task-specific elaborative feedback (experimental group) is com-pared to a simpler kind of feedback which only offers the knowledge of response (control group). After each task, the experimental group receives feedback on whether the task was solved correctly or incorrectly. If there is a second failed attempt, students will be given the correct solution with the steps to solve it (feed back). In addition, they can access help provided by the tool while working on the task (feed forward). In comparison, the control group simply receives feedback on which task was solved correctly and which incorrectly at the end of all tasks. Afterwards those students get a second chance to solve the wrong tasks. Content and assessment. The tasks cover the addition and division of fractions. After the intervention a fractions test is administered to determine the effect of the intervention on mathematical performance. For being able to answer the sec-ond and third research question, the usage and perception of feedback, is as-sessed as well. Therefore, screen recordings are used for the experimental group to capture how students interact with the teaching-learning platform and its feedback (actual usage). A questionnaire handed in after the intervention will capture the perceived constructive support and the perceived usefulness for both groups – as well as the perceived usage for the experimental group. The items on perceived constructive support and perceived usefulness were taken and adapted from Baumert et al. (2008) as well as Rakoczy et al. (2019). The items on perceived usage were newly developed for this study. Subsequent guided interviews with selected probands from the experimental group provide qualitative insight into these three constructs.

Despite the knowledge that feedback is an important driver in the learning pro-cess and elaborate feedback can support students the most, it is rarely found in school practice. Teaching-learning platforms can (probably) have a supportive effect in this case. But from an empirical point of view, very little is known about the feedback these tools offer. Therefore, this study focuses on the question of how digitally-supported practice as a central moment of teaching-learning processes in mathematics education can be successfully used to support individ-ual performance improvement of students using a teaching-learning platform and its generated feedback. The aim is to gain new insights into practicing with digi-tal media in mathematics lessons. In addition, it will be determined whether there is a discrepancy between the goal of automatically generated feedback and the perception of this feedback by students. Since the study is still in the plan-ning phase, no results can be reported yet. However, the experimental group is expected to achieve better performance results through the implementation of elaborative feedback. In addition, usage and perception are expected to have a mediating effect on students’ mathematics learning.

Barry, V. J. (2008). Using Descriptive Feedback In a Sixth Grade Mathematics Claasroom. Action Research Project, 9. Baumert, J., Blum, W., Brunner, M., Dubberke, T., Jordan, A., Klus-mann, U., Krauss, S., Kunter, M., Löwen, K., Neubrand, M., & Tsai, Y.-M. (2008). Professionswissen von Lehrkräften, kognitiv aktivierender Mathematikunterricht und die Entwicklung von mathematischer Kompetenz (COACTIV): Dokumentation der Erhebungsinstrumente. Materialien aus der Bildungsforschung: Nr. 83. Max-Planck-Inst. für Bildungsforschung. http://hdl.handle.net/hdl:11858/00-001M-0000-0023-998B-4 Cheung, A. C.K., & Slavin, R. E. (2013). The effectiveness of educa-tional technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review, 9, 88–113. https://doi.org/10.1016/j.edurev.2013.01.001 Hattie, J., & Timperley, H. (2007). The Power of Feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487 Lipnevich, A. A., & Smith, J. K. (2009). Effects of differential feedback on students' examination performance. Journal of Experimental Psychology. Applied, 15(4), 319–333. https://doi.org/10.1037/a0017841 Rakoczy, K., Pinger, P., Hochweber, J., Klieme, E., Schütze, B., & Besser, M. (2019). Formative assessment in mathematics: Mediated by feedback's perceived usefulness and students' selfefficacy. Learning and Instruction, 60, 154–165. https://doi.org/10.1016/j.learninstruc.2018.01.004 Scharnagl, S., Evanschitzky, P., Streb, J., Spitzer, M., & Hille, K. (2014). Sixth Graders Benefit from Educational Software when Learning about Fractions: A Controlled Classroom study. Numeracy, 7(1). https://doi.org/10.5038/1936-4660.7.1.4 Stein, M. (2015). Eva-CBTM: Evaluation of computer based online training programs for mathematics (2., enlarged ed.). Mathematiklernen mit digitalen Medien: Vol. 1. WTM Verl. für Wiss. Texte und Medien. http://wtm-verlag.de/ebook_download/Stein_Eva_CBTM___ISBN9783942197717.pdf Strijbos, J.-W., Narciss, S., & Dünnebier, K. (2010). Peer feedback con-tent and sender's competence level in academic writing revision tasks: Are they critical for feedback perceptions and efficiency? Learning and Instruction, 20(4), 291–303. https://doi.org/10.1016/j.learninstruc.2009.08.008 van der Kleij, F. M., Eggen, T. J.H.M., Timmers, C. F., & Veldkamp, B. P. (2012). Effects of feedback in a computer-based assessment for learning. Computers & Education, 58(1), 263–272. https://doi.org/10.1016/j.compedu.2011.07.020 Wisniewski, B., Zierer, K., & Hattie, J. (2019). The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research. Frontiers in Psychology, 10, 3087. https://doi.org/10.3389/fpsyg.2019.03087