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The Influence of User-Perceived Benefits on the Acceptance of Microlearning for Librarians' Training
Isibika, Irene Shubi; Zhu, Chang; De Smet, Egbert; Musabila, Albogast K. – Research in Learning Technology, 2023
Microlearning has shifted professional training and development and its acceptance depends on perceived user benefits. This study examines the influence of user-perceived benefits on librarians' acceptance of the microlearning approach in selected universities in Tanzania. Using a questionnaire informed by the variables of the Technology…
Descriptors: Foreign Countries, Learning Modules, Learning Activities, Library Education
Qiao, Chen; Hu, Xiao – IEEE Transactions on Learning Technologies, 2023
Free text answers to short questions can reflect students' mastery of concepts and their relationships relevant to learning objectives. However, automating the assessment of free text answers has been challenging due to the complexity of natural language. Existing studies often predict the scores of free text answers in a "black box"…
Descriptors: Computer Assisted Testing, Automation, Test Items, Semantics
Xu, Chengpei; Jia, Wenjing; Wang, Ruomei; He, Xiangjian; Zhao, Baoquan; Zhang, Yuanfang – IEEE Transactions on Learning Technologies, 2023
With the increasing popularity of open educational resources in the past few decades, more and more users watch online videos to gain knowledge. However, most educational videos only provide monotonous navigation tools and lack elaborating annotations. This makes the task of locating interesting contents time consuming. To address this limitation,…
Descriptors: Open Educational Resources, Video Technology, Instructional Films, Navigation (Information Systems)
Bozkurt, Aras; Sharma, Ramesh C. – Asian Journal of Distance Education, 2023
Generative AI is here to stay, and we need to explore the potential role of these technologies in distance education and online learning, considering both the benefits and challenges. With many potentials such as customized learning experiences, intelligent tutoring, automated grading, content creation, and personalized career advice, there are…
Descriptors: Algorithms, Artificial Intelligence, Distance Education, Electronic Learning
Rahm, Lina – Journal of Education Policy, 2023
This article argues that sociotechnical imaginaries, defined as collectively held, institutionally stabilized, and publicly performed visions of desirable sociotechnical futures, are significantly connected to visions, policies, and projects of educating citizens. These visions, policies, and projects -- or educational imaginaries -- constitute…
Descriptors: Digital Literacy, Citizenship, Computer Uses in Education, Computer Attitudes
Zhao, Ruibin; Zhuang, Yipeng; Zou, Di; Xie, Qin; Yu, Philip L. H. – Education and Information Technologies, 2023
Grading assignments is inherently subjective and time-consuming; automatic scoring tools can greatly reduce teacher workload and shorten the time needed for providing feedback to learners. The purpose of this paper is to propose a novel method for automatically scoring student responses to picture-cued writing tasks. As a popular paradigm for…
Descriptors: Artificial Intelligence, Automation, Scoring, Visual Aids
Yan, Da – Education and Information Technologies, 2023
Technology-enhanced language learning has exerted positive effects on the performance and engagement of L2 learners. Since the advent of tools based on recent advancement in artificial intelligence (AI), educators have made major strides in applying state-of-the-art technologies to writing classrooms. In November 2022, an AI-powered chatbot named…
Descriptors: Artificial Intelligence, Second Language Learning, Writing Instruction, Practicums
Pearson, Christopher; Penna, Nigel – Assessment & Evaluation in Higher Education, 2023
E-assessments are becoming increasingly common and progressively more complex. Consequently, how these longer, more complex questions are designed and marked is imperative. This article uses the NUMBAS e-assessment tool to investigate the best practice for creating longer questions and their mark schemes on surveying modules taken by engineering…
Descriptors: Automation, Scoring, Engineering Education, Foreign Countries
Marrone, Rebecca; Cropley, David H.; Wang, Z. – Creativity Research Journal, 2023
Creativity is now accepted as a core 21st-century competency and is increasingly an explicit part of school curricula around the world. Therefore, the ability to assess creativity for both formative and summative purposes is vital. However, the "fitness-for-purpose" of creativity tests has recently come under scrutiny. Current creativity…
Descriptors: Automation, Evaluation Methods, Creative Thinking, Mathematics Education
Rojas, Matias; Sáez, Cristian; Baier, Jorge; Nussbaum, Miguel; Guerrero, Orlando; Rodríguez, María Fernanda – International Journal of Artificial Intelligence in Education, 2023
Collaborative Problem-Solving Skills (CPS) have become increasingly important. Research into the development of CPS is still scarce, but there are several approaches that may be useful for its development. Specifically, providing feedback in collaborative contexts is key. In this paper, we study and develop a feedback system that uses Automated…
Descriptors: Feedback (Response), Cooperation, Problem Solving, Video Games
Philip I. Pavlik; Luke G. Eglington – Grantee Submission, 2023
This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…
Descriptors: Students, Models, Regression (Statistics), Alternative Assessment
Philip I. Pavlik; Luke G. Eglington – International Educational Data Mining Society, 2023
This paper presents a tool for creating student models in logistic regression. Creating student models has typically been done by expert selection of the appropriate terms, beginning with models as simple as IRT or AFM but more recently with highly complex models like BestLR. While alternative methods exist to select the appropriate predictors for…
Descriptors: Students, Models, Regression (Statistics), Alternative Assessment
Lixiang Yan; Lele Sha; Linxuan Zhao; Yuheng Li; Roberto Martinez-Maldonado; Guanliang Chen; Xinyu Li; Yueqiao Jin; Dragan Gaševic – British Journal of Educational Technology, 2024
Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are…
Descriptors: Educational Technology, Artificial Intelligence, Natural Language Processing, Educational Innovation
Ayfer Sayin; Mark Gierl – Educational Measurement: Issues and Practice, 2024
The purpose of this study is to introduce and evaluate a method for generating reading comprehension items using template-based automatic item generation. To begin, we describe a new model for generating reading comprehension items called the text analysis cognitive model assessing inferential skills across different reading passages. Next, the…
Descriptors: Algorithms, Reading Comprehension, Item Analysis, Man Machine Systems
Mohammed Muneerali Thottoli; Badria Hamed Alruqaishi; Arockiasamy Soosaimanickam – Contemporary Educational Technology, 2024
Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature…
Descriptors: Academic Advising, Artificial Intelligence, Technology Uses in Education, Role

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