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| Journal of Computer Assisted… | 3 |
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Direct linkElisabeth 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
Okan Bulut; Guher Gorgun; Seyma Nur Yildirim-Erbasli – Journal of Computer Assisted Learning, 2025
Background: Research shows that how formative assessments are operationalized plays a crucial role in shaping their engagement with formative assessments, thereby impacting their effectiveness in predicting academic achievement. Mandatory assessments can ensure consistent student participation, leading to better tracking of learning progress.…
Descriptors: Formative Evaluation, Academic Achievement, Student Participation, Learning Processes
Yue Huang; Joshua Wilson – Journal of Computer Assisted Learning, 2025
Background: Automated writing evaluation (AWE) systems, used as formative assessment tools in writing classrooms, are promising for enhancing instruction and improving student performance. Although meta-analytic evidence supports AWE's effectiveness in various contexts, research on its effectiveness in the U.S. K-12 setting has lagged behind its…
Descriptors: Writing Evaluation, Writing Skills, Writing Tests, Writing Instruction
