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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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McDonald, J.; Bird, R. J.; Zouaq, A.; Moskal, A. C. M. – Journal of Computer Assisted Learning, 2017
In large class settings, individualized student-teacher interaction is difficult. However, teaching interactions (e.g., formative feedback) are central to encouraging deep approaches to learning. While there has been progress in automatic short-answer grading, analysing student responses to support formative feedback at scale is arguably some way…
Descriptors: College Students, Health Sciences, Teacher Student Relationship, Large Group Instruction
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Hewson, C. – Journal of Computer Assisted Learning, 2012
To address concerns raised regarding the use of online course-based summative assessment methods, a quasi-experimental design was implemented in which students who completed a summative assessment either online or offline were compared on performance scores when using their self-reported "preferred" or "non-preferred" modes.…
Descriptors: Summative Evaluation, Followup Studies, Validity, Student Attitudes