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Michael C. Robbins; Zhuping Li – Field Methods, 2025
The Nolan Index (NI) is a normed, quantitative measure for comparing the degree of resemblance (similarity or dissimilarity) between free listings with an Excel program for calculating it. This article enhances that effort with the addition of an R program and additional applications. Free-list resemblance measures have been used to investigate…
Descriptors: Computation, Norm Referenced Tests, Comparative Analysis, Spreadsheets
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
Xin Gong; Shufan Yu; Jie Xu; Ailing Qiao; Han Han – Education and Information Technologies, 2024
Tangible programming combines the advantages of object manipulation with programmable hardware, which plays an essential role in improving programming skills. As a tool for ensuring the quality of projects and improving learning outcomes, the PDCA cycle strategy is conducive to cultivating reflective thinking. However, there is still a lack of…
Descriptors: Programming, Computer Science Education, Outcomes of Education, Reflection
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Demir, Seda; Doguyurt, Mehmet Fatih – African Educational Research Journal, 2022
The purpose of this research was to compare the performances of the Fixed Effect Model (FEM) and the Random Effects Model (REM) in the meta-analysis studies conducted through 5, 10, 20 and 40 studies with an outlier and 4, 9, 19 and 39 studies without an outlier in terms of estimated common effect size, confidence interval coverage rate and…
Descriptors: Meta Analysis, Comparative Analysis, Research Reports, Effect Size
Manuel B. Garcia – Education and Information Technologies, 2025
The global shortage of skilled programmers remains a persistent challenge. High dropout rates in introductory programming courses pose a significant obstacle to graduation. Previous studies highlighted learning difficulties in programming students, but their specific weaknesses remained unclear. This gap exists due to the predominant focus on the…
Descriptors: Programming, Introductory Courses, Computer Science Education, Mastery Learning
Mulder, J.; Raftery, A. E. – Sociological Methods & Research, 2022
The Schwarz or Bayesian information criterion (BIC) is one of the most widely used tools for model comparison in social science research. The BIC, however, is not suitable for evaluating models with order constraints on the parameters of interest. This article explores two extensions of the BIC for evaluating order-constrained models, one where a…
Descriptors: Models, Social Science Research, Programming Languages, Bayesian Statistics
Zhang, Man – Applied Linguistics, 2022
Until now, there has been very little unified analysis of metadiscourse across speech and writing. Drawing on a reflexive metadiscourse model, this article conducts a multidimensional analysis of metadiscourse across 10 spoken and written registers in a corpus of 626 texts. Two metadiscourse dimensions, participants' interaction and discourse…
Descriptors: Speech Communication, Language Variation, Written Language, Discourse Analysis
Son, Ji Y.; Blake, Adam B.; Fries, Laura; Stigler, James W. – Journal of Statistics and Data Science Education, 2021
Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…
Descriptors: Statistics Education, Introductory Courses, Teaching Methods, Data Analysis
Orr, J. Walker; Russell, Nathaniel – International Educational Data Mining Society, 2021
The assessment of program functionality can generally be accomplished with straight-forward unit tests. However, assessing the design quality of a program is a much more difficult and nuanced problem. Design quality is an important consideration since it affects the readability and maintainability of programs. Assessing design quality and giving…
Descriptors: Programming Languages, Feedback (Response), Units of Study, Computer Science Education
Finch, Holmes – Practical Assessment, Research & Evaluation, 2022
Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…
Descriptors: Data Analysis, Statistical Inference, Models, College Faculty
Wagh, Aditi; Wilensky, Uri – Journal of Science Education and Technology, 2018
Extensive research has shown that one of the benefits of programming to learn about scientific phenomena is that it facilitates learning about mechanisms underlying the phenomenon. However, using programming activities in classrooms is associated with costs such as requiring additional time to learn to program or students needing prior experience…
Descriptors: Evolution, Programming, Computer Uses in Education, Comparative Analysis
Flynt, Abby; Dean, Nema – Journal of Educational and Behavioral Statistics, 2016
Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…
Descriptors: Multivariate Analysis, Computer Software, Comparative Analysis, Programming Languages
Bey, Anis; Jermann, Patrick; Dillenbourg, Pierre – Educational Technology & Society, 2018
Computer-graders have been in regular use in the context of MOOCs (Massive Open Online Courses). The automatic grading of programs presents an opportunity to assess and provide tailored feedback to large classes, while featuring at the same time a number of benefits like: immediate feedback, unlimited submissions, as well as low cost of feedback.…
Descriptors: Comparative Analysis, Online Courses, Feedback (Response), Foreign Countries
Sentance, Sue; Waite, Jane; Kallia, Maria – Computer Science Education, 2019
Background and Context: Vygotsky's sociocultural theory emphasises the importance of language, mediation, and the transfer of skills and knowledge from the social into the cognitive plane. This perspective has influenced the development of PRIMM (Predict, Run, Investigate, Modify, Make), a structured approach to teaching programming. Objective:…
Descriptors: Computer Science Education, Teaching Methods, Comparative Analysis, Programming