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Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
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Fonseca, Samuel C.; Pereira, Filipe Dwan; Oliveira, Elaine H. T.; Oliveira, David B. F.; Carvalho, Leandro S. G.; Cristea, Alexandra I. – International Educational Data Mining Society, 2020
As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as 'Online Judges'. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, this may cause difficulties to learners that do not have the typical intrinsic motivation for…
Descriptors: Programming, Introductory Courses, Computer Science Education, Automation
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Raju, Rajeswari; Md Noh, Nur Hidayah; Ishak, Siti Nurul Hayatie; Eri, Zeti Darleena – Asian Journal of University Education, 2021
The present new norm driven by the COVID-19 pandemic has taught us to remain at home and carry our everyday activities. This pandemic has seriously made a radical shift to the Malaysian education sector as well. Educators instantly begin to adopt Open and Distance Learning (ODL). However, issues arise in courses that need a conventional setting.…
Descriptors: Foreign Countries, Educational Change, Distance Education, COVID-19
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Mike, Koby; Hazzan, Orit – Statistics Education Research Journal, 2022
Data science is a new field of research that has attracted growing interest in recent years as it focuses on turning raw data into understanding, insight, knowledge, and value. New data science education programs, which are being launched at an increasing rate, are designed for multiple education levels and populations. Machine learning (ML) is an…
Descriptors: Teaching Methods, Nonmajors, Statistics Education, Artificial Intelligence
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Riese, Emma; Bälter, Olle – ACM Transactions on Computing Education, 2022
Assessment plays an important role in education and can both guide and motivate learning. Assessment can, however, be carried out with different aims: providing the students with feedback that supports the learning (formative assessment) and judging to which degree the students have fulfilled the intended learning outcomes (summative assessment).…
Descriptors: Introductory Courses, Programming, Computer Science Education, Learning Motivation
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Lin, Yen-Yu – Taiwan Journal of TESOL, 2023
This study examined the effectiveness of guided data-driven learning (DDL) activities on helping technological university students with a lower-intermediate proficiency level to learn grammar and vocabulary topics for the TOEIC test. The question of whether inductive learners make more progress than deductive learners was also addressed. A total…
Descriptors: Grammar, Teaching Methods, Second Language Learning, English (Second Language)
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Kim, Byeongsu; Kim, Taehun; Kim, Jonghoon – Journal of Educational Computing Research, 2013
The paper-and-pencil programming strategy (PPS) is a way of representing an idea logically by any representation that can be created using paper and pencil. It was developed for non-computer majors to improve their understanding and use of computational thinking and increase interest in learning computer science. A total of 110 non-majors in their…
Descriptors: Teaching Methods, Nonmajors, Computer Science, Thinking Skills
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Battig, Michael; Shariq, Muhammad – Information Systems Education Journal, 2011
Using a previously published study of how students differentiate between computing disciplines, this study attempts to validate the original research and add additional hypotheses regarding the type of institution that the student resides. Using the identical survey instrument from the original study, students in smaller colleges and in different…
Descriptors: Computer Science, Intellectual Disciplines, College Students, Validity
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Lotriet, Hugo; Matthee, Machdel; Alexander, Patricia – African Journal of Research in Mathematics, Science and Technology Education, 2011
The career choice model of Adya and Kaiser posits the availability of technology resources as a structural element impacting on career choice. The model distinguishes between accessibility at school and at home. Based on this theoretical point of departure and by arguing a link between choice of major and choice of field of career, this paper…
Descriptors: Career Choice, Access to Information, Access to Computers, Internet