Persistence and Performance in Co-Enrollment Network Embeddings: An Empirical Validation of Tinto's Student Integration Model

Fincham, Ed; Rózemberczki, Benedek; Kovanović, Vitomir; Joksimovíc, Srécko; Jovanović, Jelena; Gašević, Dragan

doi:10.1109/tlt.2021.3059362

Cited by 5 publications

(7 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the pre-listening stage, multi-modal means such as theme-related video clips, music, multi-modal courseware, and props were used to stimulate students' multi-senses, arouse their listening interest, and guide students to actively participate in classroom activities. The prelistening prediction was guided by multi-modal means to pave the way for background knowledge and clear the hearing barrier [ 15 ]. Teachers create visual stimulation and auditory stimulus mainly by showing more modal courseware, supplemented by rich body movements or the physical display.…”

Section: Experiments Design Of Audio-visual Teaching Based On Network...mentioning

confidence: 99%

[Retracted] An Empirical Analysis of Audio‐Visual Teaching and Network Multi‐Modal Learning Environment Theory for English Majors

Gao

2022

Journal of Environmental and Public Health

View full text Add to dashboard Cite

In order to further investigate the network multi-modal learning environment to promote students’ ability to English audio-visual effects and improve the quality of teaching effect, an empirical analysis of audio-visual teaching and network multi-modal learning environment theory for English majors was proposed in the research. The 98 students were chosen as the experiment objects from two classes in the same school. They were divided into the experiment class and the control class. The students in the experiment class were taught according to the teaching model based on network multi-modal learning environment theory. SPSS19.0 software was used to analyze the scores before and after the experiment. After 3 months of experiment teaching, the average score of the post-test of the experiment class was 13.65 points, 2.23 points higher than 11.42 points before the test. The average score of the control class was 11.08 points, 0.1 points lower than 11.18 points before the test. It could be seen that the teaching method based on a network multi-modal learning environment was more conducive to improving the audio-visual performance and the teaching effectiveness of English majors.

show abstract

Section: Experiments Design Of Audio-visual Teaching Based On Network...mentioning

confidence: 99%

[Retracted] An Empirical Analysis of Audio‐Visual Teaching and Network Multi‐Modal Learning Environment Theory for English Majors

Gao

2022

Journal of Environmental and Public Health

View full text Add to dashboard Cite

show abstract

“…Teaching Digital Circuit Design With a 3-D Video Game: The Impact of Using In-Game Tools on Students' Performance [12], investigates the impact of three types of instructional in-game tools on engineering students' performance on digital circuit design tasks. Persistence and Performance in Co-Enrollment Network Embeddings: An Empirical Validation of Tinto's Student Integration Model [13], present a novel methodological approach using graph embedding techniques to capture both structural and neighborhood-based features of the co-enrollment network. In keeping with Tinto's model, we find that not only do these embedded representations of students' social network predict their final grade point average (GPA), but also are able to successfully classify students who dropout.…”

Section: An Unsupervised Ensemble Clustering Approach For the Analysi...mentioning

confidence: 99%

Real time multi feature performance analysis model for efficient prediction of student performance using neural networks

Suresh

Devi

2022

ijhs

View full text Add to dashboard Cite

The problem of student performance analysis and prediction has been well studied. There exist number of approaches to handle this issue which would use variety of features like the involvement in sports, education, academic and others. However, they suffer to achieve higher performance in predicting the performance of the student. To handle this issue, an efficient real time multi feature Performance Analysis Model (MFPAM) is presented in this article. The model consider number of features include the number of sessions the student attended, the number of seminars appeared, number of tests cleared, number of webinars accessed, number of assignments submitted, number of queries produced, number of subjects cleared in each time stamp, number of sports played, number of videos visited, number of extracurricular activities appeared and so on. By analyzing each features in different time stamp of the academic carrier, the method predict the performance of the student. The logs of student have been trained with neural network and at the test phase, the neurons perform analysis on each factor to produce support on different performance factors. At the output layer, the neurons generate set of weight measures towards various class of performance.

show abstract

“…Student integration refers to students' compatibility with the university environment due to interaction within the academic and social systems [1]. Previously, student integration was known as institutional integration [2], but recent research has used the terms student integration [3], [4].…”

Section: Introductionmentioning

confidence: 99%

“…Students have to adapt to the academic and social system on campus. Students who lack integration capacity have low GPA scores and even drop out [1].…”

Section: Introductionmentioning

confidence: 99%

Adaptation and validation the integration scale for Indonesian university students: academic and social

Dwiastuti,

Hendriani,

Andriani

2024

IJERE

View full text Add to dashboard Cite

Student integration is a student’s ability to integrate into the social and academic systems of the university. Integration of students has been shown to affect how well they do on campus, which helps them finish higher education. The integration scale (IS) measures integration ability that meets the principle of simplicity. The integration scale is formed of 16 items divided into five aspects and two factors. This study aimed to adapt and validate IS instruments for the Indonesian university student population. The research methods complied with the six-step procedures the International Test Commission set out. A total of 309 participants were undergraduate students. They were between 17 and 23 years old (mean=19.42, SD=1.11 years), with 247 females (79.94%) and 62 males (20.06%). The results of the confirmatory factor analysis revealed that a total of 16 items were valid and reliable. Three models that have acceptable fits were confirmed. The results demonstrate that the Indonesian integration scale measures undergraduate student integration with comparable precision to the original scale. This scale can identify students who require academic and social integration assistance and evaluate the institution’s role in academic development.

show abstract

Persistence and Performance in Co-Enrollment Network Embeddings: An Empirical Validation of Tinto's Student Integration Model

Cited by 5 publications

References 57 publications

[Retracted] An Empirical Analysis of Audio‐Visual Teaching and Network Multi‐Modal Learning Environment Theory for English Majors

[Retracted] An Empirical Analysis of Audio‐Visual Teaching and Network Multi‐Modal Learning Environment Theory for English Majors

Real time multi feature performance analysis model for efficient prediction of student performance using neural networks

Adaptation and validation the integration scale for Indonesian university students: academic and social

Contact Info

Product

Resources

About