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Qian, Yizhou; Lehman, James – Journal of Research on Technology in Education, 2022
This study investigated common student errors and underlying difficulties of two groups of Chinese middle school students in an introductory Python programming course using data in the automated assessment tool (AAT) Mulberry. One group of students was from a typical middle school while the other group was from a high-ability middle school. By…
Descriptors: Middle School Students, Programming, Computer Science Education, Error Patterns
Computerized Adaptive Assessment of Understanding of Programming Concepts in Primary School Children
Hogenboom, Sally A. M.; Hermans, Felienne F. J.; Van der Maas, Han L. J. – Computer Science Education, 2022
Background and Context: Valid assessment of understanding of programming concepts in primary school children is essential to implement and improve programming education. Objective: We developed and validated the Computerized Adaptive Programming Concepts Test (CAPCT) with a novel application of Item Response Theory. The CAPCT is a web-based and…
Descriptors: Computer Assisted Testing, Adaptive Testing, Programming, Knowledge Level
von Wangenheim, Christiane Gresse; Hauck, Jean C. R.; Demetrio, Matheus Faustino; Pelle, Rafael; da Cruz Alves, Nathalia; Barbosa, Heliziane; Azevedo, Luiz Felipe – Informatics in Education, 2018
The development of computational thinking is a major topic in K-12 education. Many of these experiences focus on teaching programming using block-based languages. As part of these activities, it is important for students to receive feedback on their assignments. Yet, in practice it may be difficult to provide personalized, objective and consistent…
Descriptors: Programming Languages, Programming, Grading, Outcome Measures
Jia, Jiyou; He, Yunfan – Interactive Technology and Smart Education, 2022
Purpose: The purpose of this study is to design and implement an intelligent online proctoring system (IOPS) by using the advantage of artificial intelligence technology in order to monitor the online exam, which is urgently needed in online learning settings worldwide. As a pilot application, the authors used this system in an authentic…
Descriptors: Artificial Intelligence, Supervision, Computer Assisted Testing, Electronic Learning
Guenaga, Mariluz; Eguíluz, Andoni; Garaizar, Pablo; Gibaja, Juanjo – Computer Science Education, 2021
Background and Context: Despite many initiatives to develop Computational Thinking (CT), not much is known about how early programmers develop CT and how we can assess their learning. Objective: Determine if the analysis of students' interactions with an online platform allows understanding the development of CT, how we can convert data collected…
Descriptors: Computation, Thinking Skills, Skill Development, Cognitive Tests
An Investigation of High School Students' Errors in Introductory Programming: A Data-Driven Approach
Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education
Jeske, Heimo J.; Lall, Manoj; Kogeda, Okuthe P. – Journal of Information Technology Education: Innovations in Practice, 2018
Aim/Purpose: The aim of this article is to develop a tool to detect plagiarism in real time amongst students being evaluated for learning in a computer-based assessment setting. Background: Cheating or copying all or part of source code of a program is a serious concern to academic institutions. Many academic institutions apply a combination of…
Descriptors: Plagiarism, Identification, Computer Software, Computer Assisted Testing
Calvo, Miquel; Carnicer, Artur; Cuadros, Jordi; Martori, Francesc; Miñarro, Antonio; Serrano, Vanessa – EURASIA Journal of Mathematics, Science and Technology Education, 2019
Open-ended tasks are common in Science, Technology, Engineering and Mathematics (STEM) education. However, as far as we know, no tools have been developed to assist in the assessment of the solution process of open-ended questions. In this paper, we propose the use of analysis of traces as a tool to address this need. To illustrate this approach,…
Descriptors: Computer Assisted Testing, STEM Education, Programming Languages, Undergraduate Students
Veerasamy, Ashok Kumar; D'Souza, Daryl; Laakso, Mikko-Jussi – Journal of Educational Technology Systems, 2016
This article presents a study aimed at examining the novice student answers in an introductory programming final e-exam to identify misconceptions and types of errors. Our study used the Delphi concept inventory to identify student misconceptions and skill, rule, and knowledge-based errors approach to identify the types of errors made by novices…
Descriptors: Computer Science Education, Programming, Novices, Misconceptions
Amasha, Mohamed A.; Abougalala, Rania A.; Reeves, Ahmad J.; Alkhalaf, Salem – Education and Information Technologies, 2018
The main purpose of this study is to investigate the effects of integration of online learning and assessment in synchronization form (OLASF) on students' learning performance. The study seeks to evaluate how the synchronization content with immediate assessment can affect the knowledge performance of the students. An experimental design with…
Descriptors: Online Courses, Computer Assisted Testing, Course Content, Academic Achievement
Hajjej, Fahima; Hlaoui, Yousra Bendaly; Ben Ayed, Leila Jemni – International Journal of Information and Communication Technology Education, 2017
The e-assessment, as an important part of any e-learning system, faces the same challenges and problems such as problems related to portability, reusability, adaptability, integration and interoperability. Therefore, we need an approach aiming to generate a general process of the e-assessment. The present study consists of the development of a…
Descriptors: Electronic Learning, Computer Assisted Testing, Management Systems, Computer Software
Enstrom, Emma; Kann, Viggo – ACM Transactions on Computing Education, 2017
When compared to earlier programming and data structure experiences that our students might have, the perspective changes on computers and programming when introducing theoretical computer science into the picture. Underlying computational models need to be addressed, and mathematical tools employed, to understand the quality criteria of…
Descriptors: Difficulty Level, Computer Science Education, Undergraduate Students, Programming
Martínez-Sáez, Antonio; Sevilla-Pavón, Ana; Gimeno-Sanz, Ana – Research-publishing.net, 2018
Instructors have to make important decisions regarding the type of assessment that will finally be implemented when producing online learning materials, since this has a noticeable effect in terms of the methodology, the approach, and the attitude of all the actors involved (Goertler, 2011). This study investigates students' perception of tutor…
Descriptors: Student Attitudes, Online Courses, English (Second Language), Second Language Learning
Nutbrown, Stephen; Higgins, Colin – Computer Science Education, 2016
This article explores the suitability of static analysis techniques based on the abstract syntax tree (AST) for the automated assessment of early/mid degree level programming. Focus is on fairness, timeliness and consistency of grades and feedback. Following investigation into manual marking practises, including a survey of markers, the assessment…
Descriptors: Programming, Grading, Evaluation Methods, Feedback (Response)
Casey, Kevin – Journal of Learning Analytics, 2017
Learning analytics offers insights into student behaviour and the potential to detect poor performers before they fail exams. If the activity is primarily online (for example computer programming), a wealth of low-level data can be made available that allows unprecedented accuracy in predicting which students will pass or fail. In this paper, we…
Descriptors: Keyboarding (Data Entry), Educational Research, Data Collection, Data Analysis