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Sperano, Isabelle; Shaw, Ross; Andruchow, Robert; Cobzas, Dana; Efird, Cory; Brookwell, Brian; Deng, William – Scholarship and Practice of Undergraduate Research, 2020
In a three-year, practice-based, creative research project, the team designed a video game for undergraduate biology students that aimed to find the right balance between educational content and entertainment. The project involved 7 faculty members and 14 undergraduate students from biological science, design, computer science, and music. This…
Descriptors: Video Games, Biology, Undergraduate Students, Science Instruction
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Ragazou, Vasiliki; Karasavvidis, Ilias – Themes in eLearning, 2020
The present study investigates whether embedding cueing in videotutorials for software training influences task performance. It also considers the indirect effects of cueing on cognitive load, self-efficacy, motivation, and flow. One hundred eighteen undergraduate students from a Greek Computer Science Department participated in the study which…
Descriptors: Foreign Countries, Computer Science Education, Undergraduate Students, Prompting
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Rachmatullah, Arif; Akram, Bita; Boulden, Danielle; Mott, Bradford; Boyer, Kristy; Lester, James; Wiebe, Eric – EURASIA Journal of Mathematics, Science and Technology Education, 2020
The increasing interest in computer science (CS) and CS-integrated STEM teaching and learning has created a need for assessment instruments that can be used to evaluate the efficacy of innovative instructional approaches to K-12 CS education. However, there is a lack of validated assessment tools aligned to core CS concepts for younger students.…
Descriptors: Test Construction, Test Validity, Measures (Individuals), Multiple Choice Tests
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Milovich, Michael, Jr.; Nicholson, Jennifer A.; Nicholson, Darren B. – Journal of Information Systems Education, 2020
Within the ever-changing technology and business landscape, it is imperative that students develop skills in identifying and leveraging emerging technologies to create business value in innovative and novel ways. Drawing on the Net-enabled Business Innovation Cycle framework, applied learning techniques, and current events, we developed an…
Descriptors: Technological Advancement, Management Information Systems, Computer Science Education, Business Administration Education
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Century, Jeanne; Ferris, Kaitlyn A.; Zuo, Huifang – International Journal of STEM Education, 2020
Background: As the number of computer science (CS) jobs become increasingly available in this country and computing skills become essential tools for managing all aspects of our personal lives, CS is quickly becoming an essential element of K-12 education and recently, there has been increased attention to bringing computer science to the…
Descriptors: Elementary School Students, Computer Science Education, Interdisciplinary Approach, Problem Based Learning
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Jones, Lee Kenneth; Hite, Rebecca L. – Electronic Journal for Research in Science & Mathematics Education, 2020
To ensure a robust pipeline of computer scientists worldwide, male and female students must perceive computer science (CS) as a viable field of study and career. Using expectancy-value theory (EVT) as an interpretive framework, this paper reports on a descriptive case study conducted within a CS course in a private, international high school in…
Descriptors: Foreign Countries, High School Students, Computer Science Education, Enrollment
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Mudrák, Marián; Turcáni, Milan; Reichel, Jaroslav – Journal on Efficiency and Responsibility in Education and Science, 2020
At current e-learning platforms, is often seen non-efficient usage of their possibilities when creating educational content. This article deals with the possibilities of using adaptive tools that are offered by learning management system (LMS) Moodle when creating a personalised e-course. The methodology created by the authors of the article for…
Descriptors: Individualized Instruction, Computer Science Education, Electronic Learning, Online Courses
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Luik, Piret; Lepp, Marina; Feklistova, Lidia; Säde, Merilin; Rõõm, Marili; Palts, Tauno; Suviste, Reelika; Tõnisson, Eno – International Journal of Lifelong Education, 2020
MOOCs for learning the basics of programming have become popular among people with a diverse range of backgrounds, interests and learning contexts. Studies show that learners who enrol in MOOCs tend to have different motivation from learners in traditional courses, but it is not known how motivation differs for people with different backgrounds.…
Descriptors: Online Courses, Open Education, Programming, Learning Motivation
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Okal, Gozde; Yildirim, Bekir; Timur, Serkan – Educational Policy Analysis and Strategic Research, 2020
This study aimed to determine the effect of teaching model developed on coding education on students' self-efficacy and attitude towards technology. The research was conducted on 64 students who were the 5th, 6th and 7th grades of a secondary school during the fall semester of 2018-2019 academic years. The research was designed in accordance with…
Descriptors: Programming, Computer Science Education, Grade 5, Grade 6
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Robb, Colleen C.; Rahn, David; Buffardi, Kevin – Journal of Education for Business, 2020
By framing entrepreneurship courses in the context of interdisciplinary team projects, students build important work-related skills whether they pursue an entrepreneurial path or employment after graduation. However, the traditional classroom environment is not conducive to realistic interdepartmental interactions found in most corporations or…
Descriptors: Interdisciplinary Approach, Engineering Education, Computer Software, Entrepreneurship
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Durak, Hatice Yildiz – Journal of Educational Computing Research, 2020
Learning the basic concepts of programming and its foundations is considered as a challenging task for students to figure out. It is a challenging process for lecturers to learn these concepts, as well. The current literature on programming training abounds with the examples of a wide range of methods employed. Within this context, one of the…
Descriptors: Educational Technology, Technology Uses in Education, Programming, Teaching Methods
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Šaric-Grgic, Ines; Grubišic, Ani; Šeric, Ljiljana; Robinson, Timothy J. – International Journal of Distance Education Technologies, 2020
The idea of clustering students according to their online learning behavior has the potential of providing more adaptive scaffolding by the intelligent tutoring system itself or by a human teacher. With the aim of identifying student groups who would benefit from the same intervention in AC-ware Tutor, this research examined online learning…
Descriptors: Learning Analytics, Intelligent Tutoring Systems, Grouping (Instructional Purposes), Undergraduate Students
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Lui, Debora; Kafai, Yasmin; Litts, Breanne; Walker, Justice; Widman, Sari – Computer Science Education, 2020
Background and Context: Physical computing involves complex negotiations of multiple, on and off-screen tasks, which calls for research on how to best structure collaborative work to ensure equitable learning. Objective: We focus on how pairs self-organized their multi-domain tasks in physical computing, and how their social interactions supported…
Descriptors: Cooperative Learning, High School Students, Computer Science Education, Programming
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Yao, Mengfan; Sahebi, Shaghayegh; Behnagh, Reza Feyzi – International Educational Data Mining Society, 2020
Student procrastination, as the voluntary delay of intended work despite expecting to be worse off for the delay, is an important factor with potentially negative consequences in student well-being and learning. In online educational settings such as Massive Open Online Courses (MOOCs), the effect of procrastination is considered to be even more…
Descriptors: Large Group Instruction, Online Courses, Student Behavior, Study Habits
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Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
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