NotesFAQContact Us
Collection
Advanced
Search Tips
Source
Interactive Learning…38
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 38 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Jérôme Hutain; Nicolas Michinov – Interactive Learning Environments, 2024
The role of individual feedback in (online) learning has been widely studied by researchers, but collective feedback based on quizzes and its impact on various academic outcomes has been overlooked to date. The aim of the present study was to compare the effects of displaying individual or collective feedback during an online course on students'…
Descriptors: Feedback (Response), Student Evaluation, Electronic Learning, Student Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Gwo-Jen Hwang; An-Chi Lin; Shao-Chen Chang – Interactive Learning Environments, 2024
Digital games have been used in various disciplines to enhance students' learning interest and effectiveness through the gaming contexts. However, most of the digital educational games use multiple-choice questions to confirm students' learning status, implying the challenge of understanding the actual learning status of students. Also, the gaming…
Descriptors: Game Based Learning, Academic Achievement, Student Behavior, Horticulture
Peer reviewed Peer reviewed
Direct linkDirect link
Kuang-yun Ting – Interactive Learning Environments, 2024
Feedback in online learning is essential to improve both teaching and learning. In peer feedback, students discuss their work and the various problems they encounter in their writing. However, learners may not receive constructive feedback if their classmates have lower writing proficiency. Therefore, anonymous peer feedback training was applied…
Descriptors: Student Attitudes, Peer Relationship, Feedback (Response), Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Gwo-Haur Hwang; Beyin Chen; Shih-Pei Chen – Interactive Learning Environments, 2024
This study proposed a game-based flipped teaching approach and applied it to a HTML (HyperText Markup Language) course. We developed two versions of the pre-class content testing, one of which was game-based, using a "looking-through" game, and the other which was traditional, using a multiple-choice test. We conducted a teaching…
Descriptors: Flipped Classroom, Instructional Effectiveness, Teaching Methods, Prior Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Lu-Ho Hsia; Gwo-Jen Hwang; Jan-Pan Hwang – Interactive Learning Environments, 2024
To improve students' sports skills performance, it is important to engage them in reflective practice. However, in physical classes, a teacher generally needs to face a number of students, and hence it is almost impossible to provide detailed guidance or feedback to individual students. Scholars have been trying to use Artificial Intelligence (AI)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Physical Education, Feedback (Response)
Peer reviewed Peer reviewed
Direct linkDirect link
Ainhoa Alvarez; Mikel Villamañe – Interactive Learning Environments, 2024
Assessment is a key element in any course, and providing students with a balance between formative and summative assessments is crucial. Defining such a process is a complex task for teachers and often entails a great workload. This makes it necessary to have tools to help in the assessment process definition and its monitoring. This paper first…
Descriptors: Open Source Technology, Learning Management Systems, Student Evaluation, College Students
Peer reviewed Peer reviewed
Direct linkDirect link
Thuy Thi-Nhu Ngo; Howard Hao-Jan Chen; Kyle Kuo-Wei Lai – Interactive Learning Environments, 2024
The present study performs a three-level meta-analysis to investigate the overall effectiveness of automated writing evaluation (AWE) on EFL/ESL student writing performance. 24 primary studies representing 85 between-group effect sizes and 34 studies representing 178 within-group effect sizes found from 1993 to 2021 were separately meta-analyzed.…
Descriptors: Writing Evaluation, Automation, Computer Software, English (Second Language)
Peer reviewed Peer reviewed
Direct linkDirect link
Bingxue Zhang; Yang Shi; Yuxing Li; Chengliang Chai; Longfeng Hou – Interactive Learning Environments, 2023
The adaptive learning environment provides learning support that suits individual characteristics of students, and the student model of the adaptive learning environment is the key element to promote individualized learning. This paper provides a systematic overview of the existing student models, consequently showing that the Elo rating system…
Descriptors: Electronic Learning, Models, Students, Individualized Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Saha, Sujan Kumar; Rao C. H., Dhawaleswar – Interactive Learning Environments, 2022
Assessment plays an important role in education. Recently proposed machine learning-based systems for answer grading demand a large training data which is not available in many application areas. Creation of sufficient training data is costly and time-consuming. As a result, automatic long answer grading is still a challenge. In this paper, we…
Descriptors: Middle School Students, Grading, Artificial Intelligence, Automation
Peer reviewed Peer reviewed
Direct linkDirect link
Adedoyin, Olasile Babatunde; Soykan, Emrah – Interactive Learning Environments, 2023
The World Health Organization has declared COVID-19 as a pandemic that has posed a contemporary threat to humanity. This pandemic has successfully forced global shutdown of several activities, including educational activities, and this has resulted in tremendous crisis-response migration of universities with online learning serving as the…
Descriptors: COVID-19, Pandemics, Online Courses, School Closing
Peer reviewed Peer reviewed
Direct linkDirect link
Davy Tsz Kit Ng; Jiahong Su; Jac Ka Lok Leung; Samuel Kai Wah Chu – Interactive Learning Environments, 2024
Artificial intelligence (AI) literacy has emerged to equip students with digital skills for effective evaluation, communication, collaboration, and ethical use of AI in online, home, and workplace settings. Countries are increasingly developing AI curricula to support students' technological skills for future studies and careers. However, there is…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Secondary School Students
Peer reviewed Peer reviewed
Direct linkDirect link
Agostino Marengo; Alessandro Pagano; Kamal Ahmed Soomro – Interactive Learning Environments, 2024
Soft skills are interpersonal, communication, and personal attributes that enable individuals to interact effectively with others in personal and workplace settings. Despite the significance of soft skills for career success, these skills are not necessarily taught in traditional academic settings. Consequently, education institutions must adopt…
Descriptors: Game Based Learning, Soft Skills, Student Evaluation, Instructional Effectiveness
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
Peer reviewed Peer reviewed
Direct linkDirect link
Lertnattee, Verayuth; Wangwattana, Bunyapa – Interactive Learning Environments, 2021
In the academic year of 2019, the designed personalized learning and assessment was applied to the fourth-year pharmacy students who registered for the Pharmacognosy Laboratory in the Faculty of Pharmacy, Silpakorn University. We allowed all students to do the experiment as they preferred. We created a personalized assessment that allowed the…
Descriptors: Individualized Instruction, Pharmaceutical Education, Laboratory Equipment, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Juan; Li, Zhe; Liu, Shuo-Fang; Cheng, Meng – Interactive Learning Environments, 2020
Traditional methods for conducting performance evaluations of academic courses are somewhat limited in that they are unable to account for both quantitative and qualitative data. For example, the data used to assess student performance in a typical industrial design course are generally complex, multi-criteria, multi-variable, and frequently vague…
Descriptors: Student Evaluation, College Students, Industrial Education, Design
Previous Page | Next Page »
Pages: 1  |  2  |  3