ArticleScientific reports2025
Exploring the categories of students' interest and their relationships with deep learning in technology supported environments.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Interest is not only the starting point to begin a wonderful learning journey for students, but also an important driver for deep learning and continuous progress. This study used latent profile analysis (LPA), multiple logistic regression analysis, and multivariate analysis of variance (MANOVA) to analyze the self-reported questionnaires of 634 junior high school students in China, with the aim of exploring the co-existing categories of situational interest and individual interest in technology-supported learning environments, the associated factors, and their impact on the four elements of deep learning (enjoyment of learning, cognitive commitment, relating ideas, understanding). The study found that the co-existing categories of situational interest and individual interest in technology-supported learning environments included "Medium situational interest-Low individual interest group", "Medium situational interest-Medium individual interest group", "High situational interest-Medium individual interest group", "High situational interest-High individual interest group"; grade level was correlated with the deepening and stabilizing phases of interest; all four interest categories were correlated with the four elements of deep learning; and the deepening and stabilizing phases of interest were more correlated with the four elements. The results of the study validate that there is heterogeneity in the effects of situational interest and individual interest on deep learning in technology-supported learning environments, and that "high situational interest-high individual interest" is an important factor in the occurrence of deep learning.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.