Research Article
Emilio Flores-Mamani, Arcelia-Olga Rojas-Salazar, Pedro-Basilio Tapia-Espinoza, Constantino-Miguel Nieves-Barreto, Juan Inquilla-Mamani, Ányela-Yésica Flores-Yapuchura, Gilberto Vilca-Cutipa
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep682
ABSTRACT
The use of artificial intelligence (AI) in higher education pedagogy has gained increasing relevance; however, there remains a shortage of psychometrically validated instruments capable of assessing, in a multidimensional and context-specific manner, faculty adoption of these technologies. The aim of this study was to identify the factorial structure and evaluate the psychometric properties of an instrument designed to measure AI use among university faculty. The instrument was developed based on the unified theory of acceptance and use of technology and was administered to a convenience sample of 330 university instructors. Exploratory factor analysis revealed a robust seven-factor structure explaining 66.90% of the total variance, allowing the refinement and optimization of the instrument from 50 to 30 items. The final scale demonstrated excellent overall internal consistency (Cronbach’s alpha = 0.913). It is concluded that the developed instrument is a valid and reliable tool for higher education institutions to assess and diagnose faculty levels of AI adoption, thereby facilitating the design of context-specific institutional policies and effective professional development programs in AI-enhanced pedagogy.
Keywords: artificial intelligence, university pedagogy, exploratory factor analysis, reliability
Research Article
Jesús Valverde-Berrocoso, Mario Hidalgo, Ana María Rodríguez
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep683
ABSTRACT
Teacher digital competence (TDC) is widely recognized as a key enabler of educational digitalization, yet many professional development initiatives do not lead to sustained changes in classroom practice. This study examines the contextual and organizational determinants that should inform the design and implementation of TDC programs in school education from an implementation science (IS) perspective. Drawing on the consolidated framework for implementation research 2.0, a three-round Delphi study was conducted with 23 specialists in educational technology, including teacher educators, school leaders, and system-level advisers. Through qualitative and quantitative analyses, the study developed a model that organizes the main determinants across five domains: intervention characteristics, outer setting, inner setting, characteristics of individuals, and implementation process. The findings suggest that effective TDC programs must extend beyond a narrow focus on individual skills, as their success also depends on leadership, organizational conditions, external support, contextual adaptation, and ongoing evaluation. The model provides a structured basis for designing, implementing, and evaluating programs that are realistic, context-sensitive, and sustainable. Overall, the study demonstrates the value of IS for strengthening teacher professional development in digital education.
Keywords: teacher digital competence, teacher education, implementation science, consolidated framework for implementation research 2.0, professional development
Review Article
Oksana V. Vashetina, Tatyana Shoustikova, Natalia A. Zaitseva, Yelizaveta V. Chereshneva, Mariia S. Pavlova, Zhanna M. Sizova, Andrey V. Suslov
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep684
ABSTRACT
Educational technology (ET) plays an important role in improving student learning experiences, yet no prior study has systematically examined research trends among its most influential publications. This bibliometric study analyzed the 100 most-cited articles on ET published between 2005 and 2024, drawn from the Scopus database. Results show that articles published in 2020 received the highest total citations, with the USA, Taiwan, and Australia as the most productive countries and Computers and Education as the leading source journal. Analysis of the top 20 most-cited articles identified three themes: interactive learning environments, the role of digital technologies, and the impact of the COVID-19 pandemic on ET use. Keyword co-occurrence analysis further revealed four emerging research clusters spanning technology acceptance, learning-process monitoring, distance-learning pedagogy, and post-pandemic online/blended learning models. Co-citation analysis showed that researchers most frequently drew on studies addressing individual learner characteristics and technology acceptance frameworks (TAM/UTAUT). These findings offer researchers and practitioners a consolidated overview of the field’s most impactful contributions and emerging directions.
Keywords: educational technology, most cited studies, bibliometric analysis, 100 most cited, TAM, UTAUT
Research Article
Manuel Alejandro Concha-Huarcaya, Antonio Serpa-Barrientos, Luis Alberto Sosa-Aparicio, Enrique Giovanni Pérez-Flores, Jacksaint Saintila
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep685
ABSTRACT
Online learning strategies refer to the methods and approaches students use to organize study activities, manage course content, and regulate participation in virtual learning environments. These strategies are relevant to educational technology because they provide measurable indicators that can inform instructional design, learning analytics, adaptive learning systems, and student support in online and blended courses. This study examined the psychometric properties of the online learning strategies scale (OLSS) using a psychometric network analysis approach in Peruvian university students. The sample included 520 university students (389 women = 74.8%; 131 men = 25.2%) aged 18 to 40 years. Descriptive analyses were conducted to evaluate item distributions. The psychometric network structure of the OLSS was then estimated using exploratory graph analysis with bootstrap procedures, followed by assessment of community stability and structural consistency. The results identified a four-community structure corresponding to motivation, self-control, Internet literacy, and Internet anxiety. The network showed high structural stability, with bootstrap replication values close to 1.00 for most items and high structural consistency across communities. These findings support the internal structure and reliability of the OLSS in the studied population. From an educational technology perspective, the OLSS may help instructors and instructional designers identify students requiring motivational, self-regulatory, digital literacy, or affective support in technology-enhanced learning environments.
Keywords: online learning, online learning strategies, educational technology, network analysis, psychometrics, university students
Research Article
Muhammad Noor Kholid, Rahmadani Fitri Nur Handayani, Safitri Nuraini
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep686
ABSTRACT
GeoGebra in mathematics learning can potentially be used to help students improve their mathematical communication and representation skills in solving problems. However, limited research has examined the integration of GeoGebra and contextual mathematics learning to improve these skills. The study aims to examine the effectiveness of GeoGebra in contextual mathematics learning on students’ mathematical communication and representation skills. Using a quantitative approach with a quasi-experimental design, the study involved 53 ninth-grade students from a junior high school, who were divided into experimental and control groups through purposive sampling. They participated in a five-session GeoGebra-supported contextual learning program. Data collection was conducted through a mathematical representation ability test and a mathematical communication observation sheet. Data were analyzed using descriptive statistics, independent-samples t-tests, and multivariate analysis of covariance to examine the simultaneous effects of the intervention on both dependent variables. The results revealed significant improvements in both mathematical communication and representation skills. The intervention produced a small effect on mathematical communication (Cohen’s d = 0.402) and a large effect on mathematical representation (Cohen’s d = 1.61), indicating stronger gains in students’ ability to construct and translate mathematical representations. The findings demonstrate that dynamic visualization combined with contextual problem-solving provides an effective learning environment for strengthening students’ mathematical communication and representation (Antara & Sutama, 2026; Kholid et al., 2024b; Septiani & Kholid, 2023). Unlike previous studies that primarily examined GeoGebra or contextual learning separately, the study provides empirical evidence that integrating dynamic visualization through GeoGebra with contextual learning activities can simultaneously enhance students’ mathematical communication and representation skills.
Keywords: GeoGebra, contextual learning, mathematical communication, mathematical representation, dynamic geometry software, transformation geometry
Research Article
Ahmet Sami Konca, Seden Demirtas Ilhan, Omer Faruk Akbulut
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep687
ABSTRACT
Problematic technology use in early childhood is commonly examined through parent reports and pediatric perspectives, while the role of school counselors remains underexplored. This qualitative study investigated school counselors’ perceptions and reported practices regarding problematic technology use among preschool children in Kayseri, Turkey. Data were collected through face-to-face semi-structured interviews with eight counselors working in preschools and kindergartens. Interviews included open-ended questions and a vignette-based scenario, were audio-recorded, transcribed verbatim, and analyzed through inductive thematic analysis. Four interpretive themes were identified: technology use as a developmentally sensitive and family-mediated concern; recognizing problematic use through social, behavioral, and attentional indicators; replacing screen routines with social alternatives and family limit-setting; and awareness-oriented counseling practice and the limits of current support. Counselors viewed problematic technology use as linked to family routines and visible in preschool settings through social participation, behavior, attention, and emotional regulation. Findings from this small local sample suggest that preschool counseling practice may benefit from more systematic assessment, targeted psychoeducation, and referral pathways.
Keywords: problematic technology use, educational technology, school counselors, early childhood education, Turkey
Research Article
Alejandro Valencia-Arias, Jesús Alberto Jimenez Garcia, Lelis Grabiel Palacios Silva, Sebastián Cardona-Acevedo, Sebastián Arias García, Jackeline Valencia, Luisa Yepes Ospina
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep688
ABSTRACT
Gamification and serious games are two such strategies that have seen a surge in popularity as pedagogical approaches in higher education. These strategies incorporate game elements and playful environments, with the aim of enhancing student motivation, engagement, and participation in digital and diverse learning settings. In this context, the present research aims to estimate the overall relationship between gamification, serious games, and university learning outcomes through a correlational meta-analysis of the available empirical evidence. The study employs a quantitative approach and is structured in accordance with international reporting standards, with explicit criteria for data search, selection, extraction, and synthesis that ensure analytical consistency and methodological transparency. The findings indicate that the relationship between gamification, serious games, and university learning is not a homogeneous effect, but rather a complex phenomenon conditioned by the educational context, pedagogical design, and methodological decisions in primary studies. The analysis emphasizes the significance of estimating global associations, accompanied by stability and robustness assessments. It also demonstrates the limitations of broad classifications of results in explaining the observed variability.
Keywords: gamification, serious games, university learning, correlational meta-analysis, learning outcomes
Research Article
Minnie H.-M. Hsieh, Alex Maritz, Chich-Jen Shieh
CONT ED TECHNOLOGY, Volume 18, Issue 4, Article No: ep689
ABSTRACT
This study examined whether generative AI-driven environmental education changes university students’ social norms and environmental awareness differently from conventional instruction when course content is held constant. Environmental awareness was operationalized as nature relatedness. A pre-test post-test control group quasi-experimental design was used with 257 undergraduate students enrolled in a green building environment course, 129 in the experimental group and 128 in the control group. The experimental group reached the course material through a custom ChatGPT module restricted to that material, while the control group received conventional instruction. The intervention lasted 14 weeks. Social norms were measured with a purpose-developed 10-item instrument distinguishing descriptive from injunctive norms, and nature relatedness with the 21-item nature relatedness scale. Data were analyzed with Bayesian paired samples t-tests and Bayesian ANCOVA. Both conditions produced large pre-test to post-test gains on all five dimensions, with Bayes factors above 10 to the power of 42 and effect sizes between d = 0.90 and d = 1.41. After pre-test scores were controlled, the evidence favored the absence of a group difference on every dimension: Bayes factors for adding group to the pre-test model ranged from 0.21 to 0.48, and the strongest evidence against a group effect was obtained for nature experience, BF10 = 0.24, the dimension on which an advantage for continuous access was most plausible. Men scored slightly higher than women on the nature-self dimension. The findings indicate that the quality of course content, rather than the medium through which it is delivered, accounts for the change observed here.
Keywords: generative AI, ChatGPT, environmental education, social norms, nature relatedness, Bayesian analysis