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Blaženka Divjak; Barbi Svetec; Damir Horvat – Journal of Computer Assisted Learning, 2024
Background: Sound learning design should be based on the constructive alignment of intended learning outcomes (LOs), teaching and learning activities and formative and summative assessment. Assessment validity strongly relies on its alignment with LOs. Valid and reliable formative assessment can be analysed as a predictor of students' academic…
Descriptors: Automation, Formative Evaluation, Test Validity, Test Reliability
Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
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
Richard Say; Denis Visentin; Annette Saunders; Iain Atherton; Andrea Carr; Carolyn King – Journal of Computer Assisted Learning, 2024
Background: Formative online multiple-choice tests are ubiquitous in higher education and potentially powerful learning tools. However, commonly used feedback approaches in online multiple-choice tests can discourage meaningful engagement and enable strategies, such as trial-and-error, that circumvent intended learning outcomes. These strategies…
Descriptors: Feedback (Response), Self Management, Formative Evaluation, Multiple Choice Tests
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
Bacca-Acosta, Jorge; Fabregat, Ramon; Baldiris, Silvia; Kinshuk; Guevara, Juan – Journal of Computer Assisted Learning, 2022
Background: Mobile-based assessment has been an active area of research in the field of mobile learning. Prior research has demonstrated that mobile-based assessment systems positively affect student performance. However, it is still unclear why and how these systems positively affect student performance. Objectives: This study aims to identify…
Descriptors: Academic Achievement, Electronic Learning, Handheld Devices, Computer Assisted Testing
Al-Zohbi, Gaydaa; Pilotti, Maura A. E.; Barghout, Kamal; Elmoussa, Omar; Abdelsalam, Hanadi – Journal of Computer Assisted Learning, 2023
Background: Valuable safeguards against fast-spreading conjectures about learning in times of fear and uncertainty are evidence-based approaches to the assessment of the impact of sudden and unforeseen disruptions on learning practices. The present research focused on physics learning in such times because conceptual and computational literacy in…
Descriptors: COVID-19, Pandemics, Physics, Science Education
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
Veugen, Maria Joanna; Gulikers, Judith Theresia Maria; den Brok, Perry – Journal of Computer Assisted Learning, 2022
Introduction: During the COVID-19 lockdown in 2020, teachers had to shift their teaching and assessment to online. Formative assessment (FA) can help teachers to engage, guide and monitor students' (online) learning. However, more knowledge is needed of how teachers could use the full FA process online. Methods: In this study data from 50…
Descriptors: Secondary School Teachers, Formative Evaluation, Student Evaluation, Electronic Learning
Joshua Weidlich; Aron Fink; Ioana Jivet; Jane Yau; Tornike Giorgashvili; Hendrik Drachsler; Andreas Frey – Journal of Computer Assisted Learning, 2024
Background: Developments in educational technology and learning analytics make it possible to automatically formulate and deploy personalized formative feedback to learners at scale. However, to be effective, the motivational and emotional impacts of such automated and personalized feedback need to be considered. The literature on feedback…
Descriptors: Emotional Response, Student Motivation, Feedback (Response), Automation
Jewoong Moon; Sheunghyun Yeo; Seyyed Kazem Banihashem; Omid Noroozi – Journal of Computer Assisted Learning, 2024
Background: Traditionally, understanding students' learning dynamics, collaboration, emotions, and their impact on performance has posed challenges in formative assessment. The complexity of monitoring and assessing these factors have often limited the depth and breadth of insights. Objectives: This study aims to explore the potential of…
Descriptors: Formative Evaluation, Nonverbal Communication, Outcomes of Education, Learning Analytics
Gardner, John; O'Leary, Michael; Yuan, Li – Journal of Computer Assisted Learning, 2021
Artificial Intelligence is at the heart of modern society with computers now capable of making process decisions in many spheres of human activity. In education, there has been intensive growth in systems that make formal and informal learning an anytime, anywhere activity for billions of people through online open educational resources and…
Descriptors: Artificial Intelligence, Educational Assessment, Formative Evaluation, Summative Evaluation
Gombert, Sebastian; Di Mitri, Daniele; Karademir, Onur; Kubsch, Marcus; Kolbe, Hannah; Tautz, Simon; Grimm, Adrian; Bohm, Isabell; Neumann, Knut; Drachsler, Hendrik – Journal of Computer Assisted Learning, 2023
Background: Formative assessments are needed to enable monitoring how student knowledge develops throughout a unit. Constructed response items which require learners to formulate their own free-text responses are well suited for testing their active knowledge. However, assessing such constructed responses in an automated fashion is a complex task…
Descriptors: Coding, Energy, Scientific Concepts, Formative Evaluation
Kim, Min Kyu; McCarthy, Kathryn S. – Journal of Computer Assisted Learning, 2021
Summary writing is a useful instructional tool for learning. However, summary writing is a challenge to many students. This mixed-method study examined the potential of the Student Mental Model Analyzer for Research and Teaching (SMART) system to help students produce summaries that reflect key concepts and relations in a text. SMART uses the…
Descriptors: Writing Improvement, Formative Evaluation, Technology Integration, Schemata (Cognition)
Ifenthaler, Dirk; Schumacher, Clara; Kuzilek, Jakub – Journal of Computer Assisted Learning, 2023
Background: Formative assessments are vital for supporting learning and performance but are also considered to increase the workload of teachers. As self-assessments in higher education are increasingly facilitated via digital learning environments allowing to offer direct feedback and tracking students' digital learning behaviour these…
Descriptors: Self Evaluation (Individuals), Economics Education, Business Administration Education, Faculty Workload