Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 3 |
Since 2006 (last 20 years) | 4 |
Descriptor
Cluster Grouping | 4 |
Foreign Countries | 3 |
College Students | 2 |
Feedback (Response) | 2 |
Multivariate Analysis | 2 |
Prediction | 2 |
Accuracy | 1 |
Affective Measures | 1 |
Attitude Measures | 1 |
Best Practices | 1 |
Biotechnology | 1 |
More ▼ |
Source
IEEE Transactions on Learning… | 4 |
Author
Gama, Sandra | 2 |
Jorge, Joaquim | 2 |
Barata, Gabriel | 1 |
Barnes, S.-A. | 1 |
Berrocal-Lobo, Marta | 1 |
Bimrose, J. | 1 |
Bradley, C. | 1 |
Brown, A. | 1 |
Goncalves, Daniel | 1 |
Gonçalves, Daniel | 1 |
Kaschig, A. | 1 |
More ▼ |
Publication Type
Journal Articles | 4 |
Reports - Research | 4 |
Education Level
Higher Education | 2 |
Adult Education | 1 |
Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Nabizadeh, Amir Hossein; Goncalves, Daniel; Gama, Sandra; Jorge, Joaquim – IEEE Transactions on Learning Technologies, 2022
The main challenge in higher education is student retention. While many methods have been proposed to overcome this challenge, early and continuous feedback can be very effective. In this article, we propose a method for predicting student final grades in a course using only their performance data in the current semester. It assists students in…
Descriptors: College Students, Prediction, Grades (Scholastic), Game Based Learning
Barata, Gabriel; Gama, Sandra; Jorge, Joaquim; Gonçalves, Daniel – IEEE Transactions on Learning Technologies, 2016
State of the art research shows that gamified learning can be used to engage students and help them perform better. However, most studies use a one-size-fits-all approach to gamification, where individual differences and needs are ignored. In a previous study, we identified four types of students attending a gamified college course, characterized…
Descriptors: Prediction, Performance, Profiles, Games
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
Kaschig, A.; Maier, R.; Sandow, A.; Lazoi, M.; Schmidt, A.; Barnes, S.-A.; Bimrose, J.; Brown, A.; Bradley, C.; Kunzmann, C.; Mazarakis, A. – IEEE Transactions on Learning Technologies, 2013
The level of similarity of knowledge work across occupations and industries allows for the design of supportive information and communication technology (ICT) that can be widely used. In a previous ethnographically informed study, we identified activities that can be supported to increase knowledge maturing, conceptualized as goal-oriented…
Descriptors: Learning Activities, Technology Uses in Education, Best Practices, Telephone Surveys