07/05/2026
PUBLICATION ALERT
Congratulations on your research publication, Dr. Robert Jay N. Angco
Abstract: https://so01.tci-thaijo.org/index.php/hbds/article/view/285068/182879
Abstract Aim/Purpose:Developingfacultyresearch capabilities is critical for higher education institutions seeking to enhance research productivity and academic quality. Despite widespread recognition of the importance of structured research training, empirical evidence regarding effectiveness remains limited, particularly in developing-country contexts. The rapid evolution of research methodologies, publication landscapes, and technological tools,including artificial intelligence,necessitates systematic capacity building beyond traditional mentoring. Contemporary training must address fundamental methodological competencies, as well as emerging skills in digital tools, open-access publishing, predatory-journalidentification, and ethical standards. Few studies have employed comprehensive evaluation frameworks to assess whether training programs achieve intended outcomes across learning and behavioral dimensions, limiting evidence-based decision-making for faculty development investments.Introduction/Background:This study evaluatedthe effectiveness of a structured research capability training program using the Kirkpatrick Four-Level Evaluation Model, examining participant reactions (Level 1), knowledge acquisition (Level2), behavioral change intentions and self-efficacy improvements (Level 3), and potential organizational impact (Level 4 indicator). The evaluation providedempirical evidence regarding the value of multi-topic intensive training while identifying program strengths and areasfor improvement. By applying systematic evaluation, thisstudy addsto the limited evidence on effective faculty development and provides actionable insights for institutional planning and resource allocation.Methodology:A pre-post evaluation study with 40 faculty participants assessed an intensive multi-day research capability training program covering methodology fundamentals, journal selection strategies, predatory journal identification, AI tool applications, data analysis, and academic writing through interactive methods and expert-led sessions. Data collection employed: (a) validated pre-test and post-test questionnaires (10 items each) covering methodology, ethics, journal selection, and open access; (b) structured satisfaction questionnaire with four domains on 5-point Likert scales including content delivery (8 items), facilitator performance (4 items), logistics (4 items), and learning outcomes (4 items); (c) self-efficacy scales for journal identification and ethical standards confidence; and (d) open-ended qualitative feedback. Quantitative analysis used descriptive statistics, Cohen’sdeffect sizes, and frequencies. Qualitative responses were analyzed thematically, with inter-rater reliability (kappa) =.84. Sample size for G Power analysis required a minimum of 34 participants for detecting Cohen’sdof .50effects at 80 percent power, withalpha equal to .05. All participants provided informed consent per institutional ethical requirements.Findings:The evaluation demonstrated exceptional effectiveness across outcomes, providing strong evidence at Kirkpatrick Levels 1–2 with promising indicators at Level 3–4. Knowledge gains were substantial: open access understanding increased from 12.5 to 87.5 percent (a75 percentage-point gain, Cohen’sd= 3.2); predatory journal identification improved from 85 to 92.5 percent (Cohen d= .60); ethics understanding rose from 92.5 to 97.5 percent (Cohen d= .40); methodology mastery reached 100 percent from 95 percent. Self-efficacy showed large improvements: journal identification confidence increased from a mean of3.60(SD= .97) to a mean of 4.37(SD= .54), a .77-point gain (Cohen d=1.1); ethical standards confidence rose from mean of 3.92(SD= .96) to a meanof4.50(SD= .56), (Cohen d=.70). Reduced standard deviations indicatedconvergence across competency levels;satisfaction evaluation (n=30, 75 percent response) showed unanimous positive reception,with 100 percent ratingthe overall effectiveness withscores from 4.00 to 5.00 on a 5-point scale. Domain means ranged between 4.47and 4.77, with instructor expertise as the highest (M= 4.77, SD= .43). Consistent high performance across content delivery (M= 4.63-4.73), facilitator performance (M= 4.70-4.77), logistics (M= 4.47-4.73), and learning outcomes (M= 4.60-4.70). Qualitative analysis identified three value-drivers: technology integration (18 mentions), publication strategy guidance (18 mentions), and expert instruction (12 mentions). Improvements needed included extended duration (8 mentions), methodological specialization (6 mentions), and infrastructure enhancement (5 mentions).Contribution/Impact on Society:This research provides robust evidence for the effectiveness of structured multi-topic research capability training in enhancing faculty competencies for contemporary academic research. Findings validatedcomprehensive training integrating traditional skills with emerging technological tools and publication practices. There were demonstrated improvements in knowledge and confidence across competency areas, particularly predatory journal identification and open access publishing, supporting institutional faculty development investments. Training also led to successful technology integration, especially AI applications, models, andadaptation to evolving scholarly landscapes. The comprehensive evaluation framework offers a replicable methodology for institutions assessing programs, contributing to evidence-based academic capacity building. For institutions in developing contexts, findings revealedthat well-designed intensive training achievedsubstantial improvements in faculty capabilities underresource constraints, supporting research productivity and academic quality goals.Recommendations:Institutions may implement structured research capability programs that incorporateAI tool applications, journal selection guidance, and predatory journal identification training. Program design should prioritize contemporary content, expert instructors, interactive methods, and adequate duration for comprehensive coverage. Invest in appropriate technological infrastructure and facilities to optimize learning. Implement post-training support,including mentoring networks and follow-up sessions to extend impact and facilitate sustained change. Conduct systematic evaluation using the Kirkpatrick model to assess effectiveness, identify improvements, and demonstrate return on investment.Research Limitation:Study limitations includedanimmediate post-training assessment without long-term follow-up for sustained behavioral change and organizational impact (Kirkpatrick Levels 3-4). Self-reportedmeasures may have introducedresponse bias. Thesample size of 40 participants from a single institution limits generalizability. The evaluation lacked objective behavioral observationsor actual research output measurements. Thecross-sectional design precludedtemporal stability assessment of learning gains and confidence improvements.Future Research:Longitudinal studies could examine sustained behavior change, actual research output improvements, and the organizational impact of research training interventions to validate the Kirkpatrick Levels 3 and 4 scores.