NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 45 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Jorge López González; Jesús Manuel Martínez; Maven Lomboy; Luis Expósito – Cogent Education, 2024
This article examines the relationship between emotional intelligence and ethical leadership competencies among university students. The research hypothesis was that emotional intelligence correlates positively with the exercise of good leadership. To this aim, a study was carried out with 1101 university students from Chile, Mexico and Spain who…
Descriptors: Emotional Intelligence, Leadership Qualities, Competence, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Yik, Brandon J.; Dood, Amber J.; Cruz-Ramirez de Arellano, Daniel; Fields, Kimberly B.; Raker, Jeffrey R. – Chemistry Education Research and Practice, 2021
Acid-base chemistry is a key reaction motif taught in postsecondary organic chemistry courses. More specifically, concepts from the Lewis acid-base model are broadly applicable to understanding mechanistic ideas such as electron density, nucleophilicity, and electrophilicity; thus, the Lewis model is fundamental to explaining an array of reaction…
Descriptors: Artificial Intelligence, Models, Formative Evaluation, Organic Chemistry
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Abdi, Solmaz; Khosravi, Hassan; Sadiq, Shazia; Gasevic, Dragan – International Educational Data Mining Society, 2019
The Elo rating system has been recognised as an effective method for modelling students and items within adaptive educational systems. The existing Elo-based models have the limiting assumption that items are only tagged with a single concept and are mainly studied in the context of adaptive testing systems. In this paper, we introduce a…
Descriptors: Models, Foreign Countries, College Students, Multivariate Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Eglington, Luke G.; Pavlik, Philip I., Jr. – Journal of Educational Data Mining, 2019
In recent years, there has been a proliferation of adaptive learner models that seek to predict student correctness. Improvements on earlier models have shown that separate predictors for prior successes, failures, and recent performance further improve fit while remaining interpretable. However, students who engage in "gaming" or other…
Descriptors: College Students, Student Behavior, Models, Goodness of Fit
Eglington, Luke G.; Pavlik, Philip I., Jr. – Grantee Submission, 2019
In recent years, there has been a proliferation of adaptive learner models that seek to predict student correctness. Improvements on earlier models have shown that separate predictors for prior successes, failures, and recent performance further improve fit while remaining interpretable. However, students who engage in "gaming" or other…
Descriptors: College Students, Student Behavior, Models, Goodness of Fit
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kishabale, Bashir – International Journal of Education and Development using Information and Communication Technology, 2021
The current study, guided by the cross-sectional survey method, assessed interface design quality, and its predictive ability on E-learners' post-adoption behavior in E-learning course environments. DeLone and McLean's Information Systems Success Model, Khan's E-learning Framework, and Bhattacherjee's Information System Continuance Model formed…
Descriptors: Electronic Learning, Computer Interfaces, Design, Predictive Validity
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Alkharusi, Hussain Ali; Al Sulaimani, Humaira; Neisler, Otherine – International Journal of Instruction, 2019
Critical thinking is necessary for academic success in higher education. Hence, universities seek various ways to integrate it in the programs to enhance the productivity of their graduates. This study presents the development of a predictive model for critical thinking ability using a combination of background, demographic, and psycho-educational…
Descriptors: Critical Thinking, Thinking Skills, College Students, Foreign Countries
Peer reviewed Peer reviewed
Direct linkDirect link
Zwolak, Justyna P.; Zwolak, Michael; Brewe, Eric – Physical Review Physics Education Research, 2018
The lack of an engaging pedagogy and the highly competitive atmosphere in introductory science courses tend to discourage students from pursuing science, technology, engineering, and mathematics (STEM) majors. Once in a STEM field, academic and social integration has been long thought to be important for students' persistence. Yet, it is rarely…
Descriptors: Social Networks, STEM Education, Academic Persistence, Peer Relationship
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Almeda, Ma. Victoria; Zuech, Joshua; Utz, Chris; Higgins, Greg; Reynolds, Rob; Baker, Ryan S. – Online Learning, 2018
Online education continues to become an increasingly prominent part of higher education, but many students struggle in distance courses. For this reason, there has been considerable interest in predicting which students will succeed in online courses and which will receive poor grades or drop out prior to completion. Effective intervention depends…
Descriptors: Performance Factors, Online Courses, Electronic Learning, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Hong, Ah Jeong; Kim, Hye Jeong – Asia-Pacific Education Researcher, 2018
This study involves the development and validation of a survey that measures college students' digital readiness for academic engagement in terms of their perceived digital competencies for academic work. Both exploratory and confirmatory analyses were employed to assess the factorial structure of the Digital Readiness for Academic Engagement…
Descriptors: College Students, Learning Readiness, Electronic Learning, Test Construction
Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil – International Educational Data Mining Society, 2015
A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…
Descriptors: Models, Student Behavior, Intelligent Tutoring Systems, Data Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Conijn, Rianne; Snijders, Chris; Kleingeld, Ad; Matzat, Uwe – IEEE Transactions on Learning Technologies, 2017
With the adoption of Learning Management Systems (LMSs) in educational institutions, a lot of data has become available describing students' online behavior. Many researchers have used these data to predict student performance. This has led to a rather diverse set of findings, possibly related to the diversity in courses and predictor variables…
Descriptors: Blended Learning, Predictor Variables, Predictive Validity, Predictive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Riofrio-Luzcando, Diego; Ramirez, Jaime; Berrocal-Lobo, Marta – IEEE Transactions on Learning Technologies, 2017
Data mining is known to have a potential for predicting user performance. However, there are few studies that explore its potential for predicting student behavior in a procedural training environment. This paper presents a collective student model, which is built from past student logs. These logs are first grouped into clusters. Then, an…
Descriptors: Student Behavior, Predictive Validity, Predictor Variables, Predictive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Harvey, Andrew – Australian Journal of Education, 2014
This paper examines the relative merits of early and delayed offer schemes in attracting under-represented students to university. Following the introduction of a demand-driven system and the establishment of national growth and equity targets, Australian universities have increased the number of offers made to students before the release of…
Descriptors: Foreign Countries, College Students, College Admission, Selective Admission
Peer reviewed Peer reviewed
Direct linkDirect link
Carmi, Nurit; Arnon, Sara; Orion, Nir – Environmental Education Research, 2015
The domain of environmental protection is comprised from many sub-domains as recycling, conserving water, or reducing the consumption of energy. The attitude-behavior gap is partly explained by the gap between the specificity levels of the particular measured behavior and of its antecedent(s). The present study aimed at assessing the effects of…
Descriptors: Predictor Variables, Environmental Education, Environmental Influences, Intention
Previous Page | Next Page »
Pages: 1  |  2  |  3