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Showing 136 to 150 of 592 results Save | Export
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Hunt-Isaak, Noah; Cherniavsky, Peter; Snyder, Mark; Rangwala, Huzefa – International Educational Data Mining Society, 2020
National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…
Descriptors: Textbooks, Surveys, Grade Prediction, Undergraduate Students
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Canedo, Edna Dias; Santos, Giovanni Almeida; Leite, Leticia Lopes – Informatics in Education, 2018
The teaching-learning methodology adopted in the Introduction to Computer Science classes may be a process that makes it difficult to understand the principles of programming language for undergraduate students in Computer Science and related areas, generating high failure and course drop out rates. This paper presents an analysis of the results…
Descriptors: Teaching Methods, Introductory Courses, Programming, Programming Languages
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St. John, Jeremy; St. John, Karen; St. John, Christopher – Journal of Education for Business, 2023
Teamwork skills are an important part of business school curriculum typically taught using project-based experiential methods. This paper presents best practices for teaching teamwork skills to Gen Z students using a project-based learning, peer mentoring approach. With experiential learning theory as a guide, an interdisciplinary process was…
Descriptors: Student Projects, Active Learning, Interdisciplinary Approach, Peer Relationship
Ian Patrick Heraty – ProQuest LLC, 2023
This dissertation was a comparative study of computer science in secondary schools in both Ireland and the United States. Computer science was a new subject compared to more established subjects in both Ireland and the United States. This dissertation looked at how this subject could be accessed by students in both countries. I used a document…
Descriptors: Computer Science Education, Comparative Education, High School Students, Foreign Countries
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Samuel Boguslawski; Rowan Deer; Mark G. Dawson – Information and Learning Sciences, 2025
Purpose: Programming education is being rapidly transformed by generative AI tools and educators must determine how best to support students in this context. This study aims to explore the experiences of programming educators and students to inform future education provision. Design/methodology/approach: Twelve students and six members of faculty…
Descriptors: Programming, Computer Science Education, Personal Autonomy, Learning Motivation
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Lakshminarayanan, Srinivasan; Rao, N. J. – Cogent Education, 2021
CS1 courses are designed in Indian Institutions as a lecture course of three to four credits and one credit lab course. The issues related to curriculum design, instruction design, and students' learning manifest themselves as issues in the lab programs. This situation presents the lab instructor with an opportunity to understand and address the…
Descriptors: Computer Science Education, Teaching Methods, Programming, Programming Languages
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Marckwordt, Jasmine; Muller, Alexandria; Harlow, Danielle; Franklin, Diana; Landsberg, Randall H. – Physics Teacher, 2021
Quantum computers are at the forefront of computing; however, few people understand how they work and their capabilities. We present two versions of an interactive activity designed for high school students (ages 13 to 18) that introduce a core quantum concept--"entanglement." The first version illustrates a simple connection between two…
Descriptors: Physics, Science Instruction, High School Students, Teaching Methods
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Miller, Craig S.; Settle, Amber – ACM Transactions on Computing Education, 2019
We investigate conditions in which novices make some reference errors when programming. We asked students from introductory programming courses to perform a simple code-writing task that required constructing references to objects and their attributes. By experimentally manipulating the nature of the attributes in the tasks, from identifying…
Descriptors: Error Patterns, Novices, Programming, Introductory Courses
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Dawar, Deepak; Murphy, Marianne – Information Systems Education Journal, 2020
Teaching introductory programming courses to university students who come from a varied set of academic and non-academic backgrounds is challenging. Students who are learning programming for the first time can become easily discouraged leading to procrastination that subsequently can have an unfavorable effect on their learning outcomes, and…
Descriptors: Assignments, Scaffolding (Teaching Technique), Introductory Courses, Programming
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Lyon, Louise Ann; Schatz, Colin; Green, Emily – Community College Review, 2023
Research question: For students enrolling in introductory computer science classes at community colleges, how did they experience the class in an emergency remote teaching environment, particularly in contrast to in-person instruction at the start of the semester? Methods: Semi-structured interviews were conducted with 18 students from diverse…
Descriptors: Student Experience, Student Diversity, Minority Group Students, Introductory Courses
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Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
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Singla, Adish; Theodoropoulos, Nikitas – International Educational Data Mining Society, 2022
Block-based visual programming environments are increasingly used to introduce computing concepts to beginners. Given that programming tasks are open-ended and conceptual, novice students often struggle when learning in these environments. AI-driven programming tutors hold great promise in automatically assisting struggling students, and need…
Descriptors: Programming, Computer Science Education, Task Analysis, Introductory Courses
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
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Ezeamuzie, Ndudi O. – Education and Information Technologies, 2023
Several instructional approaches have been advanced for learning programming. However, effective ways of engaging beginners in programming in K-12 are still unclear, especially among low socioeconomic status learners in technology-deprived learning environments. Understanding the learning path of novice programmers will bridge this gap and explain…
Descriptors: Programming, Constructivism (Learning), Programming Languages, Computer Science Education
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Woods, David M. – Information Systems Education Journal, 2023
Schools have implemented the high-impact practice of first-year experience (FYE) courses to assist students with the transition to college. These courses help connect new students to the school with the goal of improving retention. While students in computing majors face the same challenges as other new college students, they also face some…
Descriptors: Introductory Courses, Information Science Education, Information Technology, Career Choice
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