Abstract
Universities nowadays are confronted with the challenge of offering students sufficient formative feedback about their learning progress. Undergraduates in particular struggle in this almost impersonal learning situation, in contrast to their experience at school. Web-based trainings often do not allow a comparable formative feedback from a teacher, as current Learning Management Systems only offer basal feedback mechanisms. The Learning Management System Analyzation Kit and the Easy Snippet Feedback Edit are software tools that have been developed to overcome this shortcoming. The intuitive design of the software allows teachers to develop small feedback generating programs, which use the educational data of EDM solutions, raw data of the LMS, or just teachersâ individual records to compose individual formative feedback messages for all students. Initial evaluations show that students appreciate this new type of feedback, and that even inexperienced users can easily operate the software.
Highlights
Feedback is one of the most influential factors supporting a student’s learning [1]
In order to manage the translation of numeric information into comprehensible formative feedback, we have developed these software tools, the Learning Management System Analyzation Kit (LMSA Kit) and the Easy Snippet Feedback Edit (ESF Edit)
While teachers can certainly benefit from the insights offered by Educational Data Mining (EDM) solutions, such as the LMSA Kit, they are still not able to address all students with specific feedback
Summary
Appropriate formative feedback can help students to refine their calibration [2]; it must consider achieved or unachieved learning goals, besides incorporating proactive suggestions for the future and help for improvements [3]. Students who are well calibrated can estimate more precisely what effort is needed to achieve mastery [2]. Otherwise, they are at risk of overestimating their performance, with the result that they might invest inadequate effort in their preparation [5,6]. Educators are not in a position to satisfy the students’ need of formative feedback, because of large-scale classes and learning that occurs predominantly at home. Feedback mechanisms in current LMSs are insufficient to allow for thorough preparation and successful recalibration of learners
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