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Anagha Vaidya; Sarika Sharma – Interactive Technology and Smart Education, 2024
Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…
Descriptors: Course Evaluation, Learning Analytics, Formative Evaluation, Information Retrieval
Wenlong Yi; Xuan Huang; Sergey Kuzmin; Igor Gerasimov; Yun Luo – Education and Information Technologies, 2025
This study proposes a knowledge graph-based big data analysis model for course quality evaluation, aiming to address issues in online education course evaluations such as semantic bias, grammatical deficiencies, vocabulary limitations, false evaluations, information distortion, and imbalanced evaluation categories. The model incorporates three…
Descriptors: Electronic Learning, Online Courses, Course Evaluation, Concept Mapping
Xieling Chen; Di Zou; Haoran Xie; Gary Cheng; Zongxi Li; Fu Lee Wang – International Review of Research in Open and Distributed Learning, 2025
Massive open online courses (MOOCs) offer rich opportunities to comprehend learners' learning experiences by examining their self-generated course evaluation content. This study investigated the effectiveness of fine-tuned BERT models for the automated classification of topics in online course reviews and explored the variations of these topics…
Descriptors: MOOCs, Distance Education, Online Courses, Course Evaluation
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Lewis, Norman P. – Journalism and Mass Communication Educator, 2021
A thematic evaluation of data journalism courses resulted in a typology that parses the field and offers guidance to educators. At the center is pattern detection, preceded by data acquisition and cleaning, and followed by data representation. The typology advances academic understanding by offering a precise conceptualization that distinguishes…
Descriptors: Data Analysis, Journalism Education, Classification, Audiences
Li, Yuheng; Rakovic, Mladen; Poh, Boon Xin; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2022
Learning objectives, especially those well defined by applying Bloom's taxonomy for Cognitive Objectives, have been widely recognized as important in various teaching and learning practices. However, many educators have difficulties developing learning objectives appropriate to the levels in Bloom's taxonomy, as they need to consider the…
Descriptors: Educational Objectives, Taxonomy, Universities, Cognitive Ability
Wang, Wei; Liu, Haiwang; Wu, Yenchun Jim; Goh, Mark – Education and Information Technologies, 2023
In Massive Open Online Courses (MOOCs), learners can post both text comments and overall ratings regarding the courses. There is growing interest in assessing the consistency of online reviews and the determinants of learner satisfaction. This study analyses the disconfirmation effect between textual review topics and the determinants of learner…
Descriptors: Student Attitudes, MOOCs, Foreign Countries, Course Evaluation
Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
Kazanidis, Ioannis; Theodosiou, Theodosios; Petasakis, Ioannis; Valsamidis, Stavros – Interactive Learning Environments, 2016
Database files and additional log files of Learning Management Systems (LMSs) contain an enormous volume of data which usually remain unexploited. A new methodology is proposed in order to analyse these data both on the level of both the courses and the learners. Specifically, "regression analysis" is proposed as a first step in the…
Descriptors: Foreign Countries, Online Courses, Course Evaluation, Electronic Learning
Ben-Jacob, Marion G.; Ben-Jacob, Tyler E. – International Association for Development of the Information Society, 2014
This paper explores alternative assessment methods from the perspective of categorizations. It addresses the technologies that support assessment. It discusses initial, formative, and summative assessment, as well as objective and subjective assessment, and formal and informal assessment. It approaches each category of assessment from the…
Descriptors: Alternative Assessment, Evaluation Methods, Classification, Formative Evaluation
Demir, Yusuf; Ertas, Abdullah – Reading Matrix: An International Online Journal, 2014
Coursebook evaluation helps practitioners decide on the most appropriate coursebook to be exploited. Moreover, evaluation process enables to predict the potential strengths and weaknesses of a given coursebook. Checklist method is probably the most widely adopted way of judging coursebooks and there are plenty of ELT coursebook evaluation…
Descriptors: Check Lists, Course Evaluation, Instructional Material Evaluation, Media Selection
Brownell, Sara E.; Kloser, Matthew J. – Studies in Higher Education, 2015
Recent calls for reform have advocated for extensive changes to undergraduate science lab experiences, namely providing more authentic research experiences for students. Course-based Undergraduate Research Experiences (CUREs) have attempted to eschew the limitations of traditional "cookbook" laboratory exercises and have received…
Descriptors: Biology, Science Instruction, Undergraduate Students, Guidelines
Caird, Sally; Lane, Andy; Swithenby, Ed; Roy, Robin; Potter, Stephen – International Journal of Sustainability in Higher Education, 2015
Purpose: This research aims to examine the main findings of the SusTEACH study of the carbon-based environmental impacts of 30 higher education (HE) courses in 15 UK institutions, based on an analysis of the likely energy consumption and carbon emissions of a range of face-to-face, distance, online and information and communication technology…
Descriptors: Higher Education, Energy, Energy Conservation, Environmental Education
Romrell, Danae; Kidder, Lisa C.; Wood, Emma – Journal of Asynchronous Learning Networks, 2014
As mobile devices become more prominent in the lives of students, the use of mobile devices has the potential to transform learning. Mobile learning, or mLearning, is defined as learning that is personalized, situated, and connected through the use of a mobile device. As mLearning activities are developed, there is a need for a framework within…
Descriptors: Models, Evaluation Methods, Course Evaluation, Electronic Learning
Mazouz, Abdelkader; Crane, Keenan – Journal of Education and Learning, 2013
Establishing a link between Course Learning Outcomes (LOs) and Program Outcomes (POs) while assessing the course contents and delivery are among the most challenging issues in Higher Education. In the present study two forms were generated based on specific Course Learning Outcomes identified in the syllabus at the beginning of the teaching term:…
Descriptors: Course Evaluation, Outcomes of Education, Matrices, Course Content

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