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Xiaorui Wang; Chao Liu; Jing Guo – International Journal of Web-Based Learning and Teaching Technologies, 2025
This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…
Descriptors: Entrepreneurship, Individualized Instruction, Learning Experience, Feedback (Response)
Dake, Delali Kwasi; Gyimah, Esther – Education and Information Technologies, 2023
Text analytics in education has evolved to form a critical component of the future SMART campus architecture. Sentiment analysis and qualitative feedback from students is now a crucial application domain of text analytics relevant to institutions. The implementation of sentiment analysis helps understand learners' appreciation of lessons, which…
Descriptors: Feedback (Response), College Students, Psychological Patterns, Algorithms
Bei Cai; Ziyu He; Hong Fu; Yang Zheng; Yanjie Song – IEEE Transactions on Learning Technologies, 2025
Much research has applied automated writing evaluation (AWE) systems to English writing instruction; however, understanding how students internalize and apply this feedback to reduce writing errors is difficult, largely due to the personal and private nature of this process. Therefore, this research utilized eye-tracking technology to explore the…
Descriptors: Undergraduate Students, Majors (Students), Writing (Composition), Writing Evaluation
Delali Kwasi Dake; Godwin Kudjo Bada – Journal of Information Technology Education: Innovations in Practice, 2023
Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students' performance and ascertain successful teaching objectives. In…
Descriptors: Psychological Patterns, Artificial Intelligence, Online Surveys, Technology Integration
Alkhalifa, Amal Khalifa; Devlin, Marie; Alkhattabi, Mona – Journal of Information Technology Education: Innovations in Practice, 2022
Aim/Purpose: To encourage students' engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems -- a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their…
Descriptors: Authors, Peer Evaluation, Feedback (Response), Algorithms
Tom Bleckmann; Gunnar Friege – Knowledge Management & E-Learning, 2023
Formative assessment is about providing and using feedback and diagnostic information. On this basis, further learning or further teaching should be adaptive and, in the best case, optimized. However, this aspect is difficult to implement in reality, as teachers work with a large number of students and the whole process of formative assessment,…
Descriptors: Concept Mapping, Formative Evaluation, Automation, Feedback (Response)
Kimberly Vo; Mahbub Sarkar; Paul J. White; Elizabeth Yuriev – Chemistry Education Research and Practice, 2024
Despite problem solving being a core skill in chemistry, students often struggle to solve chemistry problems. This difficulty may arise from students trying to solve problems through memorising algorithms. Goldilocks Help serves as a problem-solving scaffold that supports students through structured problem solving and its elements, such as…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Chemistry, Science Instruction
Shian-Shyong Tseng; Tsung-Yu Yang; Wen-Chung Shih; Bo-Yang Shan – Interactive Learning Environments, 2024
In this paper, to handle the problem of the quick evolution of cyber-security attacks, we developed the iMonsters board game and proposed the attack and defense knowledge self-evolving algorithm. Three versions of the iMonsters were launched in 2013, 2017, and 2019, respectively. Accordingly, the cyber-security ontology can be refined by the…
Descriptors: Educational Games, Computer Security, Computer Science Education, Game Based Learning
Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
Liew, Tze Wei; Tan, Su-Mae; Kew, Si Na – Information and Learning Sciences, 2022
Purpose: This study aims to examine if a pedagogical agent's expressed anger, when framed as a feedback cue, can enhance mental effort and learning performance in a multimedia learning environment than expressed happiness. Design/methodology/approach: A between-subjects experiment was conducted in which learners engaged with a multimedia learning…
Descriptors: Teaching Methods, Multimedia Instruction, Psychological Patterns, Emotional Response
Tokmak, Ahmet; Yilmaz, Ali; Seker, Mustafa – Education Quarterly Reviews, 2022
This study aims to investigate the effect of using the Harezmi education model, which has been widely used in Turkey in recent years, in social studies teaching regarding computational thinking skills. Interviews were held with students and teachers seven months after the applications to determine the conceptual knowledge levels of students for…
Descriptors: Thinking Skills, Teaching Methods, Teacher Attitudes, Student Attitudes