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All Journal International Journal of Evaluation and Research in Education (IJERE)
Daniel S. Fernando
St. Anthony’s College
Education

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Student teachers’ technological pedagogical content knowledge: assessment in a private school Daniel S. Fernando; Ana Linda O. Santos; Narlie M. Labanon
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i1.37374

Abstract

This study assessed the technological pedagogical content knowledge (TPACK) among student-teachers in a private school during the academic year 2025-2026. Additionally, it examined the differences in the level of TPACK among the student teachers when grouped by demographics. A quantitative descriptive-comparative research design was employed. The study was participated in by a total of 103 student-teachers. A 47-item adopted instrument was used to collect the data, utilizing a 5-point Likert scale. The descriptive and comparative analyses were employed. Mean, standard deviation, and the Mann-Whitney U test were used. The whole process of this study adhered to the ethical guidelines. Generally, the findings showed that the student teachers obtained high mean scores (M=4.10, SD=0.50) in TPACK. Notably, their technological pedagogical knowledge was rated very high (M=4.31, SD=0.50). Additionally, the results revealed no significant differences (U=380.000, p=0.340) between male and female across all components of TPACK. However, significant differences were observed in pedagogical knowledge (U=881.000, p=0.029) and pedagogical content knowledge (U=903.000, p=0.039) when grouped according to program. The findings imply that the Department of Teacher Education is encouraged to continue to strengthen the integration of technology in pedagogy and content instruction to sustain and further enhance student teachers’ technological competence.
Distinguishing AI-generated and real images: implications for media literacy instruction Daniel S. Fernando; Kadesh Exodus T. Berdeblanco
International Journal of Evaluation and Research in Education (IJERE) Vol 15, No 5: October 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijere.v15i5.40066

Abstract

This study aimed to assess the detection accuracy and usefulness of determinants for distinguishing artificial intelligence (AI)-generated and real images among senior high school students in Western Visayas during the academic year 2025–2026. It examined the significant differences in the two mentioned constructs across students’ demographic profiles. It employed a quantitative design- the descriptive-comparative approach. A random sample of 104 students was involved, using a validated, reliability-tested 33-item researcher-made questionnaire. Descriptive and comparative statistical analyses were employed. Mean, standard deviation (SD), Mann-Whitney U test, and Kruskal-Wallis H test were used. The findings revealed that the students demonstrated a moderate level of detection accuracy (M=5.16, SD=1.61). The students rated the usefulness of the determinants as helpful (M=3.78, SD=0.74). Additionally, it was found that there is a significant difference in detection accuracy when grouped by school type [U=965.500, p=0.011] compared to its counterparts. Significant differences were found in the usefulness of determinants for distinguishing AI from real images when grouped by type of school [U=815.000, p=0.001] and frequency of use of AI [H(2)=11.989, p=0.002]. The findings of the study may provide teachers with insights into developing instructional strategies and interventions to enhance students’ critical thinking and digital literacy skills.
Co-Authors Ana Linda O. Santos Kadesh Exodus T. Berdeblanco Narlie M. Labanon