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Elizabeth Koh; Lishan Zhang; Alwyn Vwen Yen Lee; Hongye Wang – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) has the potential to revolutionize teaching and learning applications. This article examines the word cloud, a toolkit often used to scaffold teaching and learning for reflection, critical thinking, and content learning. Addressing the issues in traditional word clouds, semantic word clouds have been…
Descriptors: Vocabulary, Visual Aids, Electronic Publishing, Word Frequency
Antonio Perez-Alvarez, Ronald; Maldonado-Mahauad, Jorge; Sharma, Kshitij; Sapunar-Opazo, Diego; Perez-Sanagustin, Mar – IEEE Transactions on Learning Technologies, 2020
Recent research shows that learners who are able to self-regulate their learning show greater levels of engagement with massive open online course (MOOC) content. To improve support for learners in their self-regulatory processes, researchers have proposed technological solutions to transform recorded MOOC data into actionable knowledge. However,…
Descriptors: Self Management, Online Courses, Large Group Instruction, Educational Technology
Liu, Qingtang; Zhang, Si; Wang, Qiyun; Chen, Wenli – IEEE Transactions on Learning Technologies, 2018
Teachers' online discussion text data shed light on their reflective thinking. With the growing scale of text data, the traditional way of manual coding, however, has been challenged. In order to process the large-scale unstructured text data, it is necessary to integrate the inductive content analysis method and educational data mining…
Descriptors: Information Retrieval, Data Collection, Data Analysis, Discourse Analysis
Liu, Ming; Calvo, Rafael A.; Pardo, Abelardo; Martin, Andrew – IEEE Transactions on Learning Technologies, 2015
Engagement is critical to the success of learning activities such as writing, and can be promoted with appropriate feedback. Current engagement measures rely mostly on data collected by observers or self-reported by the participants. In this paper, we describe a learning analytic system called Tracer, which derives behavioral engagement measures…
Descriptors: Student Behavior, Learner Engagement, Writing Assignments, Visualization
Fessl, Angela; Wesiak, Gudrun; Rivera-Pelayo, Verónica; Feyertag, Sandra; Pammer, Viktoria – IEEE Transactions on Learning Technologies, 2017
This paper presents a concept for in-app reflection guidance and its evaluation in four work-related field trials. By synthesizing across four field trials, we can show that computer-based reflection guidance can function in the workplace, in the sense of being accepted as technology, being perceived as useful and leading to reflective learning.…
Descriptors: Computer Assisted Instruction, Computer Oriented Programs, Workplace Learning, Reflection
Tabuenca, Bernardo; Kalz, Marco; Ternier, Stefaan; Specht, Marcus – IEEE Transactions on Learning Technologies, 2015
Nowadays, smartphone users are constantly receiving notifications from applications that provide feedback, as reminders, recommendations or announcements. Nevertheless, there is little research on the effects of mobile notifications to foster meta-learning. This paper explores the effectiveness of mobile notifications to foster reflection on…
Descriptors: Telecommunications, Handheld Devices, Technology Uses in Education, Educational Technology
Muller, Lars; Divitini, Monica; Mora, Simone; Rivera-Pelayo, Veronica; Stork, Wilhelm – IEEE Transactions on Learning Technologies, 2015
Wearable devices and ambient sensors can monitor a growing number of aspects of daily life and work. We propose to use this context data as content for learning applications in workplace settings to enable employees to reflect on experiences from their work. Learning by reflection is essential for today's dynamic work environments, as employees…
Descriptors: Electronic Equipment, Reflection, Work Environment, Computer Assisted Instruction