Digital Commons Network^™

การสร้างพฤติกรรมการคัดแยกขยะอย่างยั่งยืนด้วยแนวทางการจัดการเรียนรู้เชิงรุก (Active Learning) สำหรับนักเรียนชั้นประถมศึกษา กรณีศึกษาโรงเรียนสวนลุมพินี เขตปทุมวัน, รวมพร กะราลัย, ธนวรรณ จันทร์ประเสริฐ, ศศิลักษณ์ ไชยจรัส, อนัญญา พรหมรักษา, วรุต วรรณวัตร, สิตานันท์ พงษ์พุฒ, พัชรีญา ใจภักดี, นุตา ศุภคต

Thai Environment

No abstract provided.

“ขยะพลาสติกจากการสั่งอาหารออนไลน์” สถานการณ์ปัญหาและแนวทางแก้ไข (ตอนที่ 1), บุญชนิต ว่องประพิณกุล

Thai Environment

No abstract provided.

ขยะพลาสติกจากการสั่งอาหารออนไลน์ (ตอนที่ 2) - ผลการสำรวจพฤติกรรมและความคิดเห็นของผู้บริโภค, บุญชนิต ว่องประพิณกุล

Thai Environment

No abstract provided.

Bridging The Gap Between Career Expectations Versus Labor Market Realities, Reinette P. Madrid, Grethel T. Ledesma, Ignatius Aryono Putranto, Jyro B. Triviño

Leadership and Strategy Faculty Publications

Most students lack awareness regarding the labor market outcomes for their chosen college majors. This study aims to answer what factors affect the career expectations of graduating students at Quezon City University and how these expectations align with the prevailing labor market situation. It employed descriptive, causal, and explanatory research using a sample of 108 respondents from fourth-year information technology students for the school year 2021 to 2022. Eight of the nine null hypotheses were rejected by employing multinomial logistic and linear regression. Student fixed effects and other labor market outcomes significantly predicted salary, estimated stability, and estimated skills in …

Fine-Tuning Large Language Models For Binary And Multiclass Target-Specific Hate Speech Detection, Sanaa Kaddoura, Sumaia Al-Kohlani

All Works

Social media platforms are widely used by individuals from diverse demographic backgrounds to share their opinions and daily experiences. The anonymity provided by these platforms has increased the prevalence of hate speech, causing significant psychological harm to targeted groups. Existing hate speech detection approaches predominantly rely on binary classification, which fails to capture the lexical and contextual diversity of hate categories, leading to the misclassification of hate against minority groups. This study addresses this limitation by evaluating the effectiveness of five large language models (LLMs) for target-specific multiclass hate speech detection across six classes. The evaluation uses a dataset of …

Generative Ai Adoption And Solvers' Popularity On Supply-Driven Crowdsourcing Platforms: The Dual Role Of Price Signals, Zimeng Zhu, Carol Hsu, Fiona Fui-Hoon Nah, Na Liu

Research Collection School Of Computing and Information Systems

Purpose – We investigate the effect of solvers’ adoption of Generative AI (GenAI) on their popularity in a supply-driven crowdsourcing platform. We also examine the impact of price signals as well as their heterogeneous impact based on the solvers’ membership duration on the platform. Design/methodology/approach – Our analysis focuses on solvers who adopt GenAI for design-related gigs on the supply-driven crowdsourcing platform. By combining propensity score matching (PSM) with multi-period difference-in-differences (DID), we examine how GenAI adoption impacts solvers’ popularity and how price signals affect this main effect. Findings – Our findings reveal that solvers who adopt GenAI tend to …

The Downstream Effect Of Gender Bias On Academic Performance And Career Aspirations Amongst Female Students In Stem Via Gender-Professional Identity Integration (G-Pii), Chi-Ying Cheng, Shuna Shiann Khoo, Shih-Fen Cheng, Yeow Leong Lee, Vandana Ramachandra Rao

Research Collection School of Social Sciences

Background Gender imbalance in STEM, characterized by a significant underrepresentation of women, remains a significant challenge. Although gender bias is a well-known contributor to women’s attrition from STEM, the psychological mechanisms linking gender bias to departure are less well understood. Our research investigates early antecedents of attrition and the psychological processes that precede leaving the STEM pathway in tertiary education. Drawing upon identity integration research, we propose that perceived gender bias exerts undermines female STEM students’ academic performance and career aspirations by reducing their Gender-Professional Identity Integration (G-PII), a construct that captures individual differences in the perceived compatibility between a …

From Post-Hoc To Pre-Assessment Evaluation: Llms As Collaborative Partners For Simulating Student Performance, Siaw Ling Lo, Ping Fan Ke, Yi Meng Lau

Research Collection School Of Computing and Information Systems

Ensuring the quality of multiple-choice questions (MCQs) remains a complex challenge in higher education, as traditional post-hoc psychometric analyses often identify flaws only after students have been negatively impacted. While Large Language Models (LLMs) offer potential for simulating student performance to validate items before delivery, they are frequently hindered by a “high-accuracy bias” that prevents larger models from realistically mimicking student errors. This paper proposes the Triadic Pedagogical Fit (TPF) framework, which triangulates Model Scale, Task Complexity via Revised Bloom’s Taxonomy, and Instructional Persona to optimize pre-assessment evaluation. Through two studies, we demonstrate that while Mid-scale (12B) models effectively mirror …

Spatialimaginer: Towards Adaptive Visual Imagination For Spatial Reasoning, Yian Li, Yang Jiao, Bin Zhu, Tianwen Qian, Shaoxiang Chen, Jingjing Chen, Yu-Gang Jiang

Research Collection School Of Computing and Information Systems

Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language models. Despite promising performance, recent multimodal large language models (MLLMs) often exhibit fragile reasoning traces in spatial intelligence tasks that involve consistent spatial state recognition. We argue that these failures stem from a mismatch between the spatial recognition mechanism and the text-only reasoning behavior of these MLLMs. Effective spatial reasoning requires low-level geometric structure to be faithfully preserved and updated throughout the reasoning process, whereas textual representations tend to abstract away precisely these critical details. …

Assessor Experiences In Cmmc Level 2 Certification Assessments: An Interpretative Phenomenological Analysis Of Role Expectations, Samuel Heuchert, John Hastings

Research & Publications

The Cybersecurity Maturity Model Certification program requires that third-party assessments be conducted under a non-consultative model. The model is intended to ensure impartiality for organizations seeking certification. While this structure defines expectations for assessor behavior, assessor experiences and interpretations of these constraints remain underexamined. The study examines the lived experiences of CMMC-Certified Assessors and how they navigate role expectations within the non-consultative model. Using Role Conflict Theory as a guiding framework, the study applied Interpretative Phenomenological Analysis (IPA) to semi-structured interviews to explore how assessors make sense of their roles. The analysis identified experiential themes that describe how assessors construct …

Specification And Internal Assessment Of A Self Reported Protective Application Use Composite Among Computer Science Undergraduates In Enugu State Nigeria, Adesegun Nurudeen Osijirin, Leonard C. Anigbo, Oliver Okechukwu

Journal of Cybersecurity Education, Research and Practice

This study specifies a Protective Application Use Composite restricted to self-reported protective application use. A cross-sectional survey provided 364 complete records from Computer Science undergraduates at four universities in Enugu State, Nigeria, from 393 distributed questionnaires. The score is the equal-weight average of five questionnaire categories: antivirus, firewall, encryption, multi-factor authentication, and virtual private network use. Reanalysis of the author-supplied item records yielded category means from 2.097 to 2.376 and internal-consistency coefficients from 0.958 to 0.971. The composite mean was 2.170, with a standard deviation of 0.469. The first component of the category-score correlation matrix explained 50.98 percent of variance. …

Haptic Technology In Networked Digital Applications: A Literature Review, Tharanitharan Chandran, Ngu War Hlaing, Athirah Mohd Ramly

Journal of Informatics and Web Engineering

Haptic-enhanced network applications provide a breakthrough merger of haptic technology with digital environments, allowing for immersive and responsive interactions. In contrast to traditional interfaces that rely primarily on visual and auditory feedback, these applications add tactile sensations, boosting user engagement in domains such as telemedicine, Virtual Reality (VR), Augmented Reality (AR), gaming, and remote collaboration. This study adopts a systematic literature review methodology to identify, filter, and analyse relevant academic sources published between 1998 to 2024, to examine accomplishments, challenges, and future directions of haptic technology in network applications. The study investigates actuator technology, tiny haptic devices, and adaptive algorithms …

A Web-Based Multi-Modal Ai Framework For Intelligent Content Moderation With Constructive Feedback, Marwah Zaid Mohammed Al-Helali, Naveen Palanichamy, Su-Cheng Haw, Subhashini Gopal

Journal of Informatics and Web Engineering

Traditional content moderation systems primarily rely on strict measures that focus on removing offending or inappropriate content without offering users any form of educational feedback or guidance. This lack of constructive interaction often leads to a poor user experience, leaving users frustrated and uninformed regarding the reasons behind content removal. Moreover, such a system fails to encourage long-term positive behavioural changes within online communities, as users do not gain insights on how to improve their conduct. This paper proposes a new constructive Artificial Intelligence (AI) intervention system that integrates a number of AI models in order to conceptualize content moderation …

Calibrated Probabilistic Predictions For Phishing Email Detection Using Sentence-Bert With Machine Learning Models, Oluwasegun Abiodun Abioye, Abraham Evwiekpaefe, Philip Odion

Journal of Informatics and Web Engineering

The growing sophistication of phishing attacks requires better detection than classic conventional filters. Previous work has focused on the accuracy, precision and recall of classifiers but there is a lack in testing well-calibrated probability predictions, which are crucial for reliable decision-making using cybersecurity systems. To fill this gap, we present in this work a phishing email detection framework that combines semantically rich Sentence-BERT all-mpnet-base-v2 model embeddings with a wide variety of machine learning classifiers. A total of nine model configurations were tested, including Sentence-BERT combined with GRU, SVM, Random Forest, Logistic Regression, k-Nearest Neighbours, Gaussian Naïve Bayes, Multi-Layer Perceptron, LightGBM …

Intelligent Telemedicine Systems: Machine Learning For Remote Diagnosis And Patient Management, Oras Baker, Kasthuri Subaramaniam, Asiah Lokman

Journal of Informatics and Web Engineering

Telemedicine has experienced significant evolution in the past 10 years from a communication-driven health service to an intelligent, data-driven environment driven by AI (artificial intelligence), ML (machine learning), IoMT (Internet of Medical Things) and cloud–edge computing. This development has been further advanced through ongoing global health challenges that have seen an ageing population, rising burden of chronic, multi-morbid conditions, healthcare specialist shortage, soaring cost of healthcare and major disruptions like the COVID-19 pandemic. Modern telehealth services are now integrating more machine learning algorithms for remote diagnosis, real-time monitoring the patient, predictive risk stratification and proactive treatment. This paper offers a …

Latino Perceptions Of Nature, Recreation, And Community Engagement In Wasatch And Summit Counties, Utah, Elsa Perez, Jessica Ulrich-Schad, Lewis Kogan, Isaac Helton

All Current Publications

This fact sheet presents results from a Utah State University study on Latino perceptions of nature, recreation, and community engagement in Utah's Wasatch and Summit counties and barriers to accessing programming. It also includes tips for increasing Latino participation in nature programs.

Ai-Generated Phishing Attacks: Emerging Threats And Detection Strategies For Security Operations Centers, Bahzad Khalid

Journal of Cybersecurity Education, Research and Practice

Artificial intelligence (AI) is transforming cybersecurity by strengthening defensive capabilities while simultaneously enabling more sophisticated phishing attacks. AI generated phishing emails increasingly evade traditional detection methods through improved grammar, contextual relevance and realistic communication styles creating significant challenges for Security Operations Centers (SOCs). This study investigates the effectiveness of current email security systems in detecting AI generated phishing emails compared with traditional phishing emails. A mixed method experimental approach was employed using controlled Gmail and Outlook environments to evaluate the detection and classification of multiple phishing scenarios. The results demonstrate that several AI generated phishing emails successfully bypassed initial security …

A Narrative-Driven, Socratic Instructional Framework For Teaching Adversarial Cognition In Cybersecurity, Joshua K. Goossen

Journal of Cybersecurity Education, Research and Practice

The Socratic method has demonstrated, in studies across law, medicine, and nursing, that dialectic structured questioning improves expert reasoning. Cybersecurity currently teaches tools and techniques but lacks Socratic dialogic leaving graduates underprepared for novel scenarios requiring cross-domain reasoning. Because law, medicine and nursing cultivate similar reasoning as security there is principled reason to expect reasoning benefits could transfer to security students. This paper argues that the correspondence warrants investigation. Investigation requires a named, teachable reasoning target analogous to clinical reasoning and we specify that target as adversarial cognition, a framework integrating adversary features, system architecture, implementation logic, governance structure, human …

Community-Based Water Management Through Cultural Ecosystem Services: Traditional Wisdom And Modern Adaptation In Senjoyo Spring, Indonesia, Puji Winarti, Sri Haryani, Sri Wardani, Langlang Handayani

Journal of Environmental Science and Sustainable Development

Small-scale freshwater ecosystems play vital ecological and cultural roles. However, community-based water management (CBWM) often lacks a clear analytical approach to integrating cultural ecosystem services (CES) and traditional ecological knowledge (TEK), limiting the practical understanding of culturally grounded governance. To address this gap, this qualitative study explores the interactions between CES and TEK, analyzes their roles within CBWM, and identifies their implications for sustainable water governance. The integration between cultural value and local ecological knowledge makes Senjoyo Spring an appropriate location for this study. Data were collected through interviews with 20 key informants, field observations, forum group discussions (FGDs), and …

Buffeted By Change, Researchers Seek Continuity And Investment: Results From The Ithaka S+R Us Researcher Survey, Chelsea Mccracken, Dylan Ruediger, Ruby Macdougall

Copyright, Fair Use, Scholarly Communication, etc.

Executive summary

The research enterprise in the United States, established after the second world war, is experiencing massive disruption. US colleges and universities are grappling with federal and state disinvestment and intervention at a time when AI and other technologies are reshaping how research is conducted and its findings are communicated. As a result, researchers at US higher education institutions are operating in an unstable environment. Against this backdrop, the findings from our survey of 4,003 researchers, fielded in late 2025, demonstrate that they remain committed to carrying out essential work and that they are doing so in innovative ways—through …

Designing For Who Actually Shows Up: A Signal Framework For Online Adult Learners In Cybersecurity And Information Technology, Chad Whistle, Mayyada Al-Hammoshi

Journal of Cybersecurity Education, Research and Practice

Online adult learners pursuing cybersecurity and information technology credentials represent one of the fastest-growing student populations in American higher education, yet the frameworks institutions use to support their success were not designed for them. This population, disproportionately drawn from the 41.9 million Americans who hold some college credit but no credential, arrives workforce-embedded, time-constrained, and skeptical of institutional systems that previously failed to serve them. Existing persistence models grounded in traditional student integration theory inadequately account for the behavioral patterns, motivational structures, and credential expectations that define this learner. This paper proposes the SIGNAL Framework (Skills-based credential architecture, Integrated AI-informed …

Navigating Text-To-Speech (Tts): Ethical Leadership In The Use Of Generative Ai For Extension, Xue A Dong, Paul A Hill

Journal of Extension

Text-to-speech (TTS) AI technology transforms written content into natural-sounding speech, offering a useful tool to enhance accessibility and inclusivity in Extension work. This article examines the role of TTS AI in bridging communication gaps, particularly for diverse and multilingual communities, and demonstrates the importance of ethical leadership in its adoption. By prioritizing diversity, equity, and inclusion, Extension professionals can leverage TTS AI to foster greater connection and engagement. Practical applications and examples are provided to guide the integration of TTS AI into programs. The article also offers recommendations for experimenting with innovative technologies to improve educational outcomes and increase the …

The Evolving Wildfire Crisis: The Need To Adapt Statewide Extension Efforts To Address Diverse Challenges, Alison L. Deak, Kathryn E. Low, Luca Carmignani, Ryan E. Tompkins, Barbara Satink Wolfson

Journal of Extension

There are many factors that contribute to wildfire preparedness in California. Although effective wildfire preparedness requires tailored regional approaches, it is crucial to understand how statewide Extension programs can address shared challenges while augmenting region-specific strategies. For the University of California Division of Agriculture and Natural Resources Fire Network to meet the growing demands for fire-related Extension programming, a team of advisors surveyed California residents to refine the goals of our Extension programs. Survey results highlight key gaps in fire-related Extension education that residents in California and beyond need to reduce their wildfire risk.

Interrater Reliability Of Software Optimized Movement Assessment With Traditional Methods And Video-Based Functional Movement Screen Scoring And Compensatory Movement Identification, Joshua Paul Verdillo, Nj Ermina, Tanya Mariel Capilla, Russel James Balane, Evriel Prince Apura, Daryl Reymon Apla-On, Ressyl Love Salvador

Philippine Journal of Physical Therapy

Introduction: The Functional Movement Screen (FMS) is a seven-part movement assessment used to identify injury risks caused by faulty biomechanics. There are three barriers in traditional FMS assessments that could affect the tool’s validity: the subjectivity of human scores that could cause bias, the need for in-person evaluations which limit access for remote patients, and the requirement of specialized training to use the tool, which makes it less accessible. This study investigates the effectiveness of SOMA, an AI-based web application that uses the MediaPipe framework to automatically assess (FMS) performances.

Methods: This study employs a quantitative, cross-sectional, comparative design to …

Service Robots With Low Anthropomorphism In Restaurants: Consumer Reactions And Implications, Ferhat Eren, Volkan Genc

Journal of Global Hospitality and Tourism

This study investigates consumer responses to low-anthropomorphic service robots in restaurant front of-house roles using the AIDUA (Artificially Intelligent Device Use Acceptance). Data from 1,268  participants were analysed using PLS-SEM. The results revealed that social impact and  anthropomorphism significantly influenced both performance and effort expectancy, while hedonic  motivation influenced only performance expectancy. Performance expectancy strongly influenced  emotions, which in turn significantly influenced both the willingness to use service robots and objections  to their use. However, effort expectancy did not significantly influence emotions. The findings validate the  AIDUA model in this context and offer practical insights for robot design and implementation.

Implementation Of The Problem-Based Learning Model On The Topic Of The Immune System To Enhance The Critical Thinking Skills Of Grade Xi B Students At Sman 1 Tojo, Nani Sofyanti, Sutrisnawati Sutrisnawati, Vita Indri Febriani, Mohammad Jamhari, Bustamin Bustamin, Raya Agni

Jurnal Pendidikan Sains

Critical-thinking skills are essential competencies for students in 21st-century learning. Preliminary classroom observations in Class XI B at SMAN 1 Tojo indicated that instruction remained predominantly teacher-centered and provided limited opportunities for students to engage in activities involving interpretation, analysis, evaluation, and inference. This study aimed to improve students’ critical-thinking skills through the implementation of Problem-Based Learning (PBL) on the immune system topic. The study employed a Classroom Action Research (CAR) design conducted over two cycles, involving 28 students in Class XI B. Data were collected using a teacher activity observation sheet and critical-thinking skills tests assessing four indicators: interpretation, …

Love And Artificial Intelligence: A Research Proposal, Bryanna M. Deatherage, Necdet Gurkan, Sandra J.E. Langeslag

Undergraduate Research Symposium

What happens when people fall in love with Artificial Intelligence (AI)? This study seeks to examine individuals who are in love with AI companions to gain a deeper insight in the cognitive and affective consequences. In addition, this study will examine the most effective forms of intervention regarding growing or reducing feelings of love toward AI. The first part of this study will be a questionnaire about the social and emotional impact of being in love with an AI companion. Three hundred participants will be recruited through online communities related to AI companions. The second part of this study will …

Gambaran Generasi Z Yang Kesepian Dalam Penggunaan Chat Ai Sebagai Pemenuhan Kebutuhan “Someone To Talk”, Ikhwanul Ihsan Armalid, Febty Zahra Arsiwi, Qisthi Fathiyyah, Ratri Mayzakky Afra Syahida

Jurnal Psikologi Sosial

This study aims to understand the experiences of Generation Z individuals who experience loneliness in utilizing Chat AI to fulfill their need for someone to talk to within a socio-emotional context. The study employed a qualitative approach using a phenomenological method involving six Generation Z participants aged 18 to 25 who had used Chat AI for emotional sharing or venting. Data were collected through semi-structured interviews and analyzed using thematic analysis. The thematic analysis yielded six main themes: the dynamics of Generation Z social interactions, experiences of loneliness in social life, patterns of Chat AI usage, Chat AI as a …

Generative Artificial Intelligence, Academic Integrity And Authentic Assessment Within An Irish University, Louise Nagle, Brigid Crowley, Laura Rafferty, Susan Horgan, Colin O'Brien

Publications

Academics need both an overarching policy on Generative Artificial Intelligence (Gen AI) use in teaching and learning, yet agency in its application across various disciplines. Clarity on the use of the technology for both students and staff is therefore a challenge and characterised by uncertainty given how its application is still unfamiliar. This research examines the organisational context in which Gen AI is being embraced and was conducted by the digital teaching support functions within an Irish university. Students and staff were surveyed (n=1,746) on various aspects of digital use within their education and workplace, including Gen AI. …

The Use Of Gadgets And Learning Motivation Among Grade Xi Students In Biology Learning At Sma Negeri 5 Palu, Yulia Citra, Mohammad Jamhari, Masrianih Masrianih, Lestari M.P Alibasyah, Mursito S. Bialangi, Yulia Windarsih

Jurnal Pendidikan Sains

This study aims to describe the profile of gadget use and learning motivation among Grade XI students in biology learning at SMA Negeri 5 Palu and to explore students’ and teachers’ experiences of gadgets as learning support tools and potential sources of digital distraction. A qualitative descriptive design was employed, supported by descriptive questionnaire profiling. A total of 74 students completed a 50-item questionnaire on gadget use and learning motivation, while 10 students and two biology teachers participated in semi-structured interviews. Questionnaire data were analyzed using frequencies and percentages, while interview data were analyzed thematically. The descriptive findings showed that …