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Xieling Chen; Di Zou; Gary Cheng; Haoran Xie – Education and Information Technologies, 2024
The rise of massive open online courses (MOOCs) brings rich opportunities for understanding learners' experiences based on analyzing learner-generated content such as course reviews. Traditionally, the unstructured textual data is analyzed qualitatively via manual coding, thus failing to offer a timely understanding of the learner's experiences.…
Descriptors: Artificial Intelligence, Semantics, Course Evaluation, MOOCs
Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2024
Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…
Descriptors: Student Evaluation, Computer Assisted Testing, Artificial Intelligence, Comprehension
Priti Oli – ProQuest LLC, 2024
This dissertation focuses on strategies and techniques to enhance code comprehension skills among students enrolled in introductory computer science courses (CS1 and CS2). We propose a novel tutoring system, "DeepCodeTutor," designed to improve the code comprehension abilities of novices. DeepCodeTutor employs scaffolded self-explanation…
Descriptors: Reading Comprehension, Tutoring, Scaffolding (Teaching Technique), Automation
Andersen, Nico; Zehner, Fabian; Goldhammer, Frank – Journal of Computer Assisted Learning, 2023
Background: In the context of large-scale educational assessments, the effort required to code open-ended text responses is considerably more expensive and time-consuming than the evaluation of multiple-choice responses because it requires trained personnel and long manual coding sessions. Aim: Our semi-supervised coding method eco (exploring…
Descriptors: Foreign Countries, Achievement Tests, International Assessment, Secondary School Students
Oliveira Moraes, Laura; Pedreira, Carlos Eduardo – IEEE Transactions on Learning Technologies, 2021
Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…
Descriptors: Computer Science Education, Semantics, Coding, Matrices
Stéphane Favier; Jean-Luc Dorier – Educational Studies in Mathematics, 2024
In this research, our objective is to characterize the problem-solving procedures of primary and lower secondary students when they solve problems in real class conditions. To do so, we rely first on the concept of heuristics. As this term is very polysemic, we exploit the definition proposed by Rott (2014) to develop a coding manual and thus…
Descriptors: Heuristics, Semantics, Student Evaluation, Mathematics Skills
Höppner, Frank – International Educational Data Mining Society, 2021
Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…
Descriptors: Coding, Classification, Programming, Computer Science Education
Andrea Domínguez-Lara; Wulfrano Arturo Luna-Ramírez – International Association for Development of the Information Society, 2022
The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…
Descriptors: Programming, Coding, Computer Software, Programming Languages
Huang, Xiaoyi; Kim, Nayoung; Christianson, Kiel – Language Learning, 2019
When introducing new words in a second language (L2), presenting vocabulary with concurrent gestures might facilitate learners' recollection of new words. Previous research has suggested that this gestural advantage might hold only for gestures that overlap with the semantics of the words. Dual coding theory predicts that learners should learn…
Descriptors: Nonverbal Communication, Vocabulary Development, Second Language Learning, Coding
Chung, Cheng-Yu; Awad, Nayif; Hsiao, I-Han – Australasian Journal of Educational Technology, 2021
Although numerous studies have demonstrated different ways that augmented reality (AR) can assist students to understand the learning content via contextualised visualisation, less explored is its effect on collaborative problem-solving (CPS) in computer programming. This study aims to investigate how AR affects a CPS in a programming task. We…
Descriptors: Problem Solving, Problem Based Learning, Cooperative Learning, Computer Simulation
Lee, Yew-Jin; Wan, Dongsheng – Research in Science Education, 2022
There has been a longstanding interest in the kinds of scientific knowledge that primary science learners must know and be able to do, which comprise the intellectual demands in this subject. These prescriptions chiefly take guidance from national curriculum documents, especially in the form of their learning outcomes (LO) or learning standards.…
Descriptors: Semantics, Science Education, Outcomes of Education, Elementary School Students
Hamouda, Sally; Edwards, Stephen H.; Elmongui, Hicham G.; Ernst, Jeremy V.; Shaffer, Clifford A. – Computer Science Education, 2020
Background and Context: Recursion in binary trees has proven to be a hard topic. There was not much research on enhancing student understanding of this topic. Objective: We present a tutorial to enhance learning through practice of recursive operations in binary trees, as it is typically taught post-CS2. Method: We identified the misconceptions…
Descriptors: Computer Science Education, Programming, Coding, Student Attitudes
Ma, Yingbo; Katuka, Gloria Ashiya; Celepkolu, Mehmet; Boyer, Kristy Elizabeth – International Educational Data Mining Society, 2022
Collaborative learning is a complex process during which two or more learners exchange opinions, construct shared knowledge, and solve problems together. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. If intelligent systems could predict…
Descriptors: Middle School Students, Cooperative Learning, Prediction, Peer Relationship
Hagge, Julia – English Teaching: Practice and Critique, 2021
Purpose: The purpose of this paper is to examine the ways in which early adolescent programmers embed meaning in their digital media created within an online programming community called Scratch. Design/methodology/approach: The author completed an 18-month descriptive case study with 5 early adolescent participants. The research design included a…
Descriptors: Semiotics, Programming Languages, Social Media, Computer Software
Cai, Zhiqiang; Siebert-Evenstone, Amanda; Eagan, Brendan; Shaffer, David Williamson; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Coding is a process of assigning meaning to a given piece of evidence. Evidence may be found in a variety of data types, including documents, research interviews, posts from social media, conversations from learning platforms, or any source of data that may provide insights for the questions under qualitative study. In this study, we focus on text…
Descriptors: Semantics, Computational Linguistics, Evidence, Coding

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