NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20260
Since 20250
Since 2022 (last 5 years)12
Since 2017 (last 10 years)32
Source
Interactive Learning…32
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 32 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Xia, Xiaona – Interactive Learning Environments, 2023
The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…
Descriptors: Learning Analytics, Decision Making, Regression (Statistics), Bayesian Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
O. S. Adewale; O. C. Agbonifo; E. O. Ibam; A. I. Makinde; O. K. Boyinbode; B. A. Ojokoh; O. Olabode; M. S. Omirin; S. O. Olatunji – Interactive Learning Environments, 2024
With the advent of technological advancement in learning, such as context-awareness, ubiquity and personalisation, various innovations in teaching and learning have led to improved learning. This research paper aims to develop a system that supports personalised learning through adaptive content, adaptive learning path and context awareness to…
Descriptors: Cognitive Style, Individualized Instruction, Learning Processes, Preferences
Peer reviewed Peer reviewed
Direct linkDirect link
Xia, Xiaona – Interactive Learning Environments, 2023
Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…
Descriptors: Interaction, Intervention, Student Behavior, Educational Environment
Peer reviewed Peer reviewed
Direct linkDirect link
Ju-Chieh Huang – Interactive Learning Environments, 2024
This research integrated cooperative inquiry strategies to implement blended learning and analyzes the learning effects based on the perspectives of goal setting theory and well-being theory. Blended learning combines the advantages of classroom teaching and online learning and enables students to review material to further their understanding.…
Descriptors: Blended Learning, Cooperative Learning, Inquiry, Goal Orientation
Peer reviewed Peer reviewed
Direct linkDirect link
Luyu Zhu; Jia Hao; Jianhou Gan – Interactive Learning Environments, 2024
Nowadays, Massive Open Online Courses (MOOC) has been gradually accepted by the public as a new type of education and teaching method. However, due to the lack of timely intervention and guidance from educators, learners' performance is not as effective as it could be. To address this problem, predicting MOOC learners' performance and providing…
Descriptors: MOOCs, Academic Achievement, Prediction, Bayesian Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Wu, Lin-Jung; Chang, Kuo-En – Interactive Learning Environments, 2023
To achieve adaptive learning, a dynamic assessment system equipped with a cognitive diagnosis was developed for this study, which adopts a three-stage model of diagnosis-intervention-assessment. To examine how this system influenced spatial geometry learning, the study used a quasi-experimental method to investigate student learning outcomes…
Descriptors: Cognitive Measurement, Alternative Assessment, Spatial Ability, Geometry
Peer reviewed Peer reviewed
Direct linkDirect link
Constance A. Lightner; Carin A. Lightner-Laws – Interactive Learning Environments, 2024
As COVID-19 continues to impact various business sectors, university administrators have steadily pushed for all academic units to resume on campus operations and activities; conversely, faculty and students have expressed increased interest in continuing online teaching/learning. We aim to mitigate this "tug-of-war" between…
Descriptors: Blended Learning, Flexible Scheduling, Business Administration Education, Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Pi, Zhongling; Yang, Jiumin; Hu, Weiping; Hong, Jianzhong – Interactive Learning Environments, 2022
An emerging body of research has focused on students' creativity in group contexts, with the assumption that students could be inspired by peers' ideas. Although students' openness and attention to peers' ideas are claimed to play important roles in their creativity in group settings, there is little empirical research that tests this assumption.…
Descriptors: Personality Traits, Creativity, Attention, Peer Relationship
Peer reviewed Peer reviewed
Direct linkDirect link
Xing, Wanli; Pei, Bo; Li, Shan; Chen, Guanhua; Xie, Charles – Interactive Learning Environments, 2023
Engineering design plays an important role in education. However, due to its open nature and complexity, providing timely support to students has been challenging using the traditional assessment methods. This study takes an initial step to employ learning analytics to build performance prediction models to help struggling students. It allows…
Descriptors: Learning Analytics, Engineering Education, Prediction, Design
Peer reviewed Peer reviewed
Direct linkDirect link
Meng, Lingling; Zhang, Mingxin; Zhang, Wanxue; Chu, Yu – Interactive Learning Environments, 2021
Bayesian knowledge tracing model (BKT) is a typical student knowledge assessment method. It is widely used in intelligent tutoring systems. In the standard BKT model, all knowledge and skills are independent of each other. However, in the process of student learning, they have a very close relation. A student may understand knowledge B better when…
Descriptors: Bayesian Statistics, Intelligent Tutoring Systems, Student Evaluation, Knowledge Level
Peer reviewed Peer reviewed
Direct linkDirect link
Alshurideh, Muhammad; Al Kurdi, Barween; Salloum, Said A.; Arpaci, Ibrahim; Al-Emran, Mostafa – Interactive Learning Environments, 2023
Despite the plethora of m-learning acceptance studies, few have tackled the importance of examining the actual use of m-learning systems from the lenses of social influence, expectation-confirmation, and satisfaction. Additionally, most of the prior technology adoption literature tends to use the structural equation modeling (SEM) technique in…
Descriptors: Electronic Learning, Prediction, Least Squares Statistics, Structural Equation Models
Peer reviewed Peer reviewed
Direct linkDirect link
Rezaei, Mohammadsadegh; Bobarshad, Hossein; Badie, Kambiz – Interactive Learning Environments, 2021
The development of information technology and social networks has created new opportunities to access lifelong learning in the form of informal learning. In an informal learning environment, learning takes place via Communities of Practice (CoP). The learning success factors in online CoPs are learners' similarity in learning interests and…
Descriptors: Prediction, Electronic Learning, Communities of Practice, Information Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Wu, Jiun-Yu; Hsiao, Yi-Cheng; Nian, Mei-Wen – Interactive Learning Environments, 2020
This paper demonstrated the use of the supervised Machine Learning (ML) for text classification to predict students' final course grades in a hybrid Advanced Statistics course and exhibited the potential of using ML classified messages to identify students at risk of course failure. We built three classification models with training data of 76,936…
Descriptors: Social Media, Discussion Groups, Artificial Intelligence, Classification
Peer reviewed Peer reviewed
Direct linkDirect link
Delaval, Marine; Michinov, Nicolas; Le Bohec, Olivier; Le Hénaff, Benjamin – Interactive Learning Environments, 2017
The aim of this study was to examine how social or temporal-self comparison feedback, delivered in real-time in a web-based training environment, could influence the academic performance of students in a statistics examination. First-year psychology students were given the opportunity to train for a statistics examination during a semester by…
Descriptors: Mathematics Achievement, Statistics, Self Evaluation (Individuals), Feedback (Response)
Peer reviewed Peer reviewed
Direct linkDirect link
Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
Previous Page | Next Page »
Pages: 1  |  2  |  3