Lester Gilbert

Research on digital protest often treats visibility and engagement as temporally uniform by aggregating social media activity across extended periods. This approach obscures how political moments shape which messages become widely amplified. Addressing this event-contingent visibility problem, this study examines how event context structures patterns of visibility in protest communication on Twitter within a semi-authoritarian media environment. Using a high-visibility corpus of the most-retweeted tweets from 21 major political protest events in Thailand during 2021, the study combines thematic content analysis with a four-way ANOVA to analyze how event context, content themes, media formats, and posting time interact to shape retweet visibility. Visibility is conceptualized not as a stable behavioral tendency but as a contingent outcome shaped by political salience, affective alignment, and platform affordances. The findings show that event context accounts for the largest share of variance in retweet visibility, while the effects of content themes and media formats are conditional and event-dependent. These results indicate that visible connective action is episodic and that affective amplification operates in context-sensitive ways. The study refines theories of digital protest by conceptualizing visibility as an event-contingent process and highlights the analytical value and limits of high-visibility sampling.

This study examines how Generative AI and knowledge-mapping tools support student learning and engagement in programming education. A quasi-experimental design was conducted with 30 undergraduate students enrolled in an object-oriented programming course, where participants used both tools across a four-week intervention. Data were collected through task performance and learner perception surveys. The results indicate that students reported higher ease of use and immediate support when using Generative AI, while knowledge mapping was associated with stronger support for conceptual understanding and reflective learning in later stages. These findings suggest that the two approaches support different aspects of learning, with Generative AI facilitating rapid clarification and knowledge-mapping tools encouraging structured conceptual engagement. The study contributes to the e-learning field by providing empirical insight into how different forms of learning support function within the same instructional context. Rather than positioning the tools as direct alternatives, the findings highlight their complementary pedagogical roles and offer guidance for integrating adaptive AI support with structured learning approaches in programming education.

This study explores how connecting reading and writing through a process-genre approach enhances EFL learners’ academic writing competence. Based on quantitative and qualitative data, the study demonstrates that students made statistically significant improvements across seven writing traits, with the most substantial gains observed in discourse-level features—interestingness, organization, content, and cohesion. These developments were supported by students’ growing genre awareness acquired through scaffolded reading and analyzing of model texts, collaborative and independent writing tasks, and reflective activities. The findings also reveal how students systematically applied genre knowledge to their own compositions, particularly in understanding writing contexts, communicative purposes, and audience expectations. While improvements in linguistic accuracy and appropriacy were more moderate, students reported that they gained more confidence in writing. Through engagement with the reading and writing activities, students could observe how meaning is constructed in texts and apply these insights into their writing. This study underscores the pedagogical significance of connecting reading and writing within a process-genre instruction to enhance meaningful writing development.

The academic performance of learners can be measured by determining the learning results with the intended learning outcomes (ILOs). ILOs principles have encouraged learners to improve their competencies. The existing approaches for evaluating learner capacity lack a correlation between the actual learning outcomes and the ILOs. This study has proposed a new self-assessment model that allows learners to realize their ILO achievement during the learning processes towards enhancing their competencies. The Self-Regulated Learning Management (SRLM) system, implemented the ILO-based Self-Assessment Model (ISAM), has been developed for this research. The personalized learning paths in SRLM are constructed based on Bloom’s taxonomy, the Structure of Observed Learning Outcome (SOLO), and the Constructive alignment. The experimental study was conducted on ninety-two ( N = 92) university learners learning in the Database Management course. They were asked to complete a voluntary survey rating their achievement on learning outcomes of the course. The results showed that learners who were provided the ILO achievement information during the learning processes performed better academically than their peers in the same class. This conclusion was derived from t test analyses on the dataset of learners’ test scores in the experimental course and is statistically significant. Simultaneously, most learners who participated in the research expressed satisfaction with the proposed model.

Communication skills are soft skills critical for students’ development in educational institutions in the digital age. This study aims to determine the feasibility and practicality of a learning model, which combines digital storytelling with a metacognitive strategy called the DSTMC model. This learning model utilized digital storytelling as a primary learning step and integrated metacognitive strategies to monitor the thinking process to improve students’ communication, such as listening, speaking, reading, writing, and presentation skills. The research was conducted through case studies at a regional, southern Thailand university. The data were collected from 30 undergraduate participants. The research instruments were expert validation, pre-/post-test data, and a self-assessment questionnaire. The study showed that the DSTMC learning model is an alternative teaching method to improve communication skills, including listening, speaking, reading, and writing. The results of students’ test scores and self-assessments provide significant evidence indicating that it increases their learning and retention of information. The paper concludes with suggestions for using various strategies and motivating activities to encourage learners’ communication proficiency. Future research should investigate the creation of a system to track how learners improve their communication skills.

Digital games are a powerful tool for the presentation of food cultural heritage. A digital game was designed and developed to raise and enhance young people’s interest in and knowledge of Thai food cultural heritage, currently an under-researched field. The platform game was played on a mobile device and required the collection of food ingredients appropriate to popular cuisine in four Thai regions while overcoming obstacles. A sample (N=61) of young people (mean age=19 years) played the game, and the differences in their pre and post-test knowledge of and interest in Thai food and its cultural heritage were analyzed. The findings showed a highly significant increase in interest in and knowledge of Thai food cultural heritage, and did so despite the opinion of some participants that learning games were less interesting than conventional games, or that games were not a good way of raising interest in cultural heritage.

The success and quality of an educational or training system is assessed by its match to the competences it claims to develop. In this research, we propose a conceptual model of contextualized competence (or learning outcome), being a learner’s capability with respect to some subject matter. We also suggest a controlled vocabulary of capability verbs, based upon Merrill’s theory insight that a particular capability should be associated with a particular type of subject matter. At this stage, the model is deployed as a subject matter graph without contextualization in the domain of programming fundamentals. The implemented tool associates learning resources (mainly html links) with the domain knowledge structures, offering graph creation and visualization, resource suggestions, and learning paths. Future work will include learning outcomes and related context, and will evaluate user satisfaction and accessibility.