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Sarwar, Sohail; García-Castro, Raul; Qayyum, Zia Ul; Safyan, Muhammad; Munir, Rana Faisal – International Association for Development of the Information Society, 2017
Learner categorization has a pivotal role in making e-learning systems a success. However, learner characteristics exploited at abstract level of granularity by contemporary techniques cannot categorize the learners effectively. In this paper, an architecture of e-learning framework has been presented that exploits the machine learning based…
Descriptors: Student Characteristics, Profiles, Courseware, Electronic Learning
Herrmann, Kim Jesper; Bager-Elsborg, Anna; Parpala, Anna – Scandinavian Journal of Educational Research, 2017
While focus on quality in Danish higher education has been growing in recent years, limited attention has been devoted to developing and thoroughly validating instruments that allow collecting data about university students' perceptions of the teaching-learning environment. Based on data from a large sample of Danish university students, a Danish…
Descriptors: Educational Environment, Questionnaires, Learning Strategies, Outcome Measures
Bañeres, David; Clarisó, Robert; Jorba, Josep; Serra, Montse – IEEE Transactions on Learning Technologies, 2014
The synthesis of digital circuits is a basic skill in all the bachelor programmes around the ICT area of knowledge, such as Computer Science, Telecommunication Engineering or Electrical Engineering. An important hindrance in the learning process of this skill is that the existing educational tools for the design of circuits do not allow the…
Descriptors: Electronics, Design, Program Validation, Electronic Learning
Merchie, Emmelien; Van Keer, Hilde; Vandevelde, Sabrina – Journal of Psychoeducational Assessment, 2014
Independently learning from informative texts becomes increasingly important from the age of 11. Little information is available, however, on (a) how and to what extent late elementary education students already apply specific text-learning strategies, and (b) whether different learner profiles can already be distinguished. In this study, a…
Descriptors: Learning Strategies, Grade 5, Grade 6, Profiles
Law, Dennis C. S.; Meyer, Jan H. F. – Quality in Higher Education, 2010
A Chinese translation of the Inventory of Learning Styles (ILS), a quantitative instrument employed mainly in Western higher education contexts for collecting students' feedback on their learning patterns (in the form of students' processing strategies, regulation strategies, learning orientations and conceptions of learning), was adapted and…
Descriptors: Feedback (Response), Quality Control, Factor Analysis, Foreign Countries
Velayutham, Sunitadevi; Aldridge, Jill; Fraser, Barry – International Journal of Science Education, 2011
Students' motivational beliefs and self-regulatory practices have been identified as instrumental in influencing the engagement of students in the learning process. An important aim of science education is to empower students by nurturing the belief that they can succeed in science learning and to cultivate the adaptive learning strategies…
Descriptors: Learning Strategies, Construct Validity, Grade 8, Science Education
Samuelstuen, Marit S.; Braten, Ivar; Valas, Harald – Scandinavian Journal of Educational Research, 2007
This study examined contextual effects in Norwegian 10th-grade students' reports on cognitive and metacognitive strategies when using the Cross-Curricular Competencies (CCC) instrument. The CCC was first administered as the final task in a long (three-hour) testing session in the Organisation for Economic Co-operation and Development Program for…
Descriptors: Learning Strategies, Metacognition, Student Evaluation, Cognitive Measurement

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