Self-Perception and Psychological Well-Being as Determinants of Classroom Behavior of Students With and Without Learning Disability

R.K., Veni; Merlene, Annie Marie

doi:10.1177/09731342221122840

Cited by 1 publication

(1 citation statement)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In previous studies that have analyzed the performance or opinions of students with learning difficulties, the definition of participants with learning disabilities has mostly been based on clinical diagnoses (Sakiz et al, 2015;Gaspar et al, 2016;Ben-Naim et al, 2017;Veni and Merlene, 2022) or the participants have been students who have obtained low results in tests of learning competencies (Alesi et al, 2014). There have been only some studies for assessing of self-perceptions of learning disabilities in inclusive education (Rothman and Cosden, 1995;Rijumol et al, 2011).…”

Section: Students' Learning Difficultiesmentioning

confidence: 99%

Students’ digital addiction and learning difficulties: shortcomings of surveys in inclusion

Seema

Varik-Maasik

2023

Front. Educ.

View full text Add to dashboard Cite

Students have been distance learning to a considerable extent during the Covid years and the primary concerns are teenagers’ learning difficulties, digital addiction and long screen time. Our aim was thus to study teenagers’ perceived learning difficulties, digital addiction and screen time. The current study was a part of a larger e-survey. The data were collected across Estonia from 8,486 teenagers who studied in the inclusive education system during spring 2022. The students were 11–20 years old. While analysing the data, we had to exclude the answers of 315 students. Those students had answered carelessly or inaccurately, had written an inaccurate age, illogical answers or similar answers throughout the test. We studied teenagers’ level of learning difficulties, digital addiction and screen time. The study shows positive correlations between learning difficulties, digital addiction and screen time. Digital addiction and screen time predict 11% of the variability of perceived learning difficulties scores based on a Linear Regression model. The model shows a poor prediction for students whose scores are very different from the mean. We describe the weaknesses of an e-survey method in inclusive education. Linear statistical models predict well for average students, but do not predict well for respondents who are very different from the mean. The so-called residuals need special attention or, paradoxically, exclusion from the statistical analysis. The outliers are often the students who need help in the inclusive system. Here, we will share our insights, what we have learned as researchers from conducting the study. We cannot collect reliable data about special needs students with any wide scale e-survey if we do not address the developmentally heterogeneous group of students and their needs while participating in the survey. This is significant for study reliability as well as gathering data from children with special needs.

show abstract