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Sharaff, Aakanksha; Nagwani, Naresh Kumar – International Journal of Web-Based Learning and Teaching Technologies, 2020
A multi-label variant of email classification named ML-EC[superscript 2] (multi-label email classification using clustering) has been proposed in this work. ML-EC[superscript 2] is a hybrid algorithm based on text clustering, text classification, frequent-term calculation (based on latent dirichlet allocation), and taxonomic term-mapping…
Descriptors: Electronic Mail, Classification, Taxonomy, Indexes
Dorodchi, Mohsen; Dehbozorgi, Nasrin; Fallahian, Mohammadali; Pouriyeh, Seyedamin – Informatics in Education, 2021
Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…
Descriptors: Computer Science Education, Computer Software, Teaching Methods, Undergraduate Students
Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Tahereh Firoozi; Okan Bulut; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The proliferation of large language models represents a paradigm shift in the landscape of automated essay scoring (AES) systems, fundamentally elevating their accuracy and efficacy. This study presents an extensive examination of large language models, with a particular emphasis on the transformative influence of transformer-based models, such as…
Descriptors: Turkish, Writing Evaluation, Essays, Accuracy
Benjamin B. Hoar; Roshini Ramachandran; Marc Levis-Fitzgerald; Erin M. Sparck; Ke Wu; Chong Liu – Journal of Chemical Education, 2023
In education, space exists for a tool that valorizes generic student course evaluation formats by organizing and recapitulating students' views on the pedagogical practices to which they are exposed. Often, student opinions about a course are gathered using a general comment section that does not solicit feedback concerning specific course…
Descriptors: Chemistry, Science Instruction, Large Group Instruction, Teaching Methods
Fronza, Ilenia; Corral, Luis; Pahl, Claus – Informatics in Education, 2020
Computer programming skills have been growing as a professional competence also to unqualified end-users who need to develop software in their professional practice. Quality evaluation models of end-user-developed products are still scarce. In this paper, we propose a metric that leverages "When", a condition typically found in…
Descriptors: Computer Software, Computer Software Evaluation, Difficulty Level, Programming Languages
Dwi Fitria Al Husaeni; Isma Widiaty; Budi Mulyanti; Ade Gafar Abdullah; Lala Septem Riza; Amay Suherman; Dwi Novia Al Husaeni – Informatics in Education, 2025
This study aims to provide a descriptive and bibliometric analysis of the trend of artificial intelligence (AI) application in the development of computational thinking (CT) skills in publications from 2007 to 2024. A total of 191 articles were obtained from Scopus database with certain keywords, and analyzed using Biblioshiny and VOSviewer. The…
Descriptors: Artificial Intelligence, Trend Analysis, Bibliometrics, Thinking Skills
Zilong Zhong; Hui Guo; Kun Qian – Education and Information Technologies, 2024
This study leverages bibliometric analysis through the bibliometrix R-package to dissect the expansive influence of machine learning on education, a field where machine learning's adaptability and data-processing capabilities promise to revolutionize teaching and learning methods. Despite its potential, the integration of machine learning in…
Descriptors: Bibliometrics, Programming Languages, Artificial Intelligence, Technology Uses in Education
Kristina Litherland; Anders Kluge – Computer Science Education, 2024
Background and Context: We explore the potential for understanding the processes involved in students' programming based on studying their behaviour and dialogue with each other and "conversations" with their programs. Objective: Our aim is to explore how a perspective of inquiry can be used as a point of departure for insights into how…
Descriptors: Programming, Programming Languages, Secondary School Students, Computer Science Education
Weiss, Charles J. – Biochemistry and Molecular Biology Education, 2022
This article reports a workshop from the 2021 IUBMB/ASBMB Teaching Science with Big Data conference held virtually in June 2021 where participants learned to explore and visualize large quantities of protein PBD data using Jupyter notebooks and the Python programming language. This activity instructs participants using Jupyter notebooks, Python…
Descriptors: Visual Aids, Programming Languages, Data Analysis, Science Instruction
Thakur, Khusbu; Kumar, Vinit – New Review of Academic Librarianship, 2022
A vast amount of published scholarly literature is generated every day. Today, it is one of the biggest challenges for organisations to extract knowledge embedded in published scholarly literature for business and research applications. Application of text mining is gaining popularity among researchers and applications are growing exponentially in…
Descriptors: Information Retrieval, Data Analysis, Research Methodology, Trend Analysis
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
Peabody, Michael R. – Measurement: Interdisciplinary Research and Perspectives, 2023
Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical…
Descriptors: Programming Languages, Algorithms, Heuristics, Mathematical Models
Lijin Zhang; Xueyang Li; Zhiyong Zhang – Grantee Submission, 2023
The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…
Descriptors: Computer Software, Programming Languages, Data Analysis, Visual Aids
Kuroki, Masanori – Journal of Economic Education, 2023
As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…
Descriptors: Statistics Education, Teaching Methods, Competition, Prediction

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