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30,938 Article Results

A survey of retrieval algorithms in ad and content recommendation systems

10.11591/ijece.v16i3.pp1518-1530
Yu Zhao , Fang Liu , Yuan Yuan , Yifan Dang
This paper presents a survey of retrieval algorithms used in advertising recommendation and organic content recommendation systems. Modern digital platforms rely on retrieval-based models to efficiently match users with relevant advertisements or personalized content. This survey reviews key techniques including inverted index methods, collaborative filtering, content-based filtering, hybrid recommendation models, and the two-tower neural network architecture widely used in large-scale recommendation systems. The paper compares the objectives, data utilization strategies, and evaluation metrics of ad targeting and organic retrieval systems. Practical challenges such as cold-start problems, data quality, scalability, and privacy considerations are also discussed. This survey further highlights the growing connection between industrial recommendation pipelines and emerging retrieval mechanisms used in large language model (LLM) systems. This survey provides insights into the design principles of modern retrieval systems and outlines future research directions at the intersection of recommendation systems and LLM.
Volume: 16
Issue: 3
Page: 1518-1530
Publish at: 2026-06-01

Student satisfaction in student affairs management: the role of cross-functional cooperation in Hainan, China

10.11591/ijere.v15i3.39033
Erlin Tian , Supot Rattanapun
Student affairs management (SAM) is increasingly expected to deliver timely, coherent, and student-centered services, yet satisfaction remains uneven in Chinese universities because students experience SAM as an integrated system rather than isolated units. This study asks whether cross-functional cooperation (CFC) explains how service quality, service gaps, and students’ psychological and engagement factors translate into satisfaction with SAM in Hainan Province, China. Using a cross-sectional survey of 250 undergraduate and postgraduate students from ten public and private universities, the study applies partial least squares–structural equation modeling (PLS-SEM) with 5,000-sample bootstrapping to test direct and mediating effects. Results show that CFC is the strongest predictor of satisfaction (β=0.419, p<0.001). Service gaps reduce satisfaction (β=−0.217, p<0.001), while psychological and engagement factors increase satisfaction (β=0.206, p<0.001). Service quality has no direct effect but operates through CFC, indicating that coordination is required to convert service inputs into positive experiences. The findings highlight governance reforms that institutionalize cross-department coordination, shared case management, and gap monitoring to improve SAM effectiveness under Hainan’s reform context.
Volume: 15
Issue: 3
Page: 1963-1970
Publish at: 2026-06-01

ChatGPT in the university classroom: perceptions, perceived usefulness and use intentions among undergraduate students

10.11591/ijere.v15i3.38709
Vidnay Noel Valero-Ancco , Yolanda Lujano-Ortega
The objectives of the present study are to analyze university students’ perceptions of and attitudes toward ChatGPT as a support tool for learning, as well as the user profiles derived from their technological acceptance, were analyzed. A quantitative, nonexperimental and cross-sectional design was applied to a non-probabilistic convenience sample of 438 undergraduate students, and a validated questionnaire composed of three dimensions compatibility with learning styles, ease of use and perceived usefulness, and continued use intentions was used. The data were analyzed with hierarchical cluster analysis (Ward method). The results reveal three groups of users: i) enthusiasts, with highly favorable perceptions and high use intentions; ii) moderate users, who exhibit partial acceptance; and iii) critical or disconnected users, who have a negative view of the tool. Taken together, the findings confirm that perceived usefulness, ease of use and trust are determining factors in the intention to use ChatGPT. This study provides empirical evidence on the diversity of attitudes toward generative artificial intelligence (GenAI) in university contexts and highlights the need to promote institutional strategies of critical digital literacy and teacher training for its ethical and pedagogical integration.
Volume: 15
Issue: 3
Page: 2073-2081
Publish at: 2026-06-01

Narrative comprehension in 5-year-old Vietnamese-speaking children using the multilingual assessment instrument for narratives

10.11591/ijere.v15i3.38932
Nguyen Thi Hoang Yen , Ben Phạm , Hang Pham , Van Pham , Phuong Nguyen , Phuong Bui
This study addresses how elicitation modes and socio-demographic factors influence narrative macrostructure understanding in 5-year-old Vietnamese-speaking children. A convenience sampling of 311 typically developing children were assessed using the multilingual assessment instrument for narratives (MAIN). Narrative comprehension was evaluated through 10 standardized questions for both retelling (cat story) and storytelling (baby goats story) modes. Findings revealed a significant advantage for retelling (M=7.21, SD=2.31) over storytelling (M=5.73, SD=2.50; p<.001), highlighting the role of linguistic scaffolding. While children mastered identifying character goals, challenges remained in explaining internal states and making causal inferences. Narrative comprehension was independent of gender, location, and general communication skills, but significantly influenced by maternal education level (p<.05). Vietnamese narrative development follows universal patterns, yet deep comprehension is shaped by specific environmental inputs. This study establishes a normative baseline for narrative skills within the Vietnamese preschool curriculum and provides a validated tool for speech and language therapists to facilitate early identification and targeted interventions.
Volume: 15
Issue: 3
Page: 1908-1918
Publish at: 2026-06-01

Radar-based gesture recognition simulation for unmanned aerial vehicles command interpretation

10.11591/ijece.v16i3.pp1227-1235
Denny Dermawan , Freddy Kurniawan , Yenni Astuti , Paulus Setiawan , Lasmadi Lasmadi , Uyuunul Mauidzoh , Bambang Sudibya
Radar-based gesture recognition has emerged as a robust alternative to vision-based systems, particularly in environments where lighting and privacy pose challenges. This study presents a simulation approach for recognizing hand gestures to control unmanned aerial vehicles (UAVs) using radar signals. Five discrete gestures, i.e., TakeOff, Land, MoveForward, TurnLeft, and stop, were defined and modeled in MATLAB to generate synthetic radar signals. From each sample, four time-frequency domain features were extracted: duration, maximum amplitude, dominant frequency, and root mean square (RMS). A dataset of 500 samples (100 per class) was classified using three supervised learning models: support vector machine (SVM), k-nearest neighbors (k-NN), and decision tree. The k-NN classifier achieved the highest accuracy of 96%, demonstrating the feasibility of lightweight classifiers for gesture recognition using low-complexity features. These results highlight the potential of radar-based interfaces to replace traditional remote controls in UAV operation. The proposed simulation framework contributes to the development of intuitive, non-contact human-machine interaction systems.
Volume: 16
Issue: 3
Page: 1227-1235
Publish at: 2026-06-01

Brain tumor detection using VGG-16 model

10.11591/ijai.v15.i3.pp2337-2346
Aicha Oussous , Abderrahmane Ez-zahout , Soumia Ziti
Research in medical image analysis, specifically through deep convolutional networks, addresses the challenges of manually analyzing large magnetic resonance imaging (MRI) image volumes for brain tumor detection. The manual analysis is time-consuming, tedious, and prone to inaccuracies due to subtle visual similarities between normal tissue and tumor cells. This research aims to automate tumor detection, increasing accuracy and efficiency in medical treatments. This study aimed to develop a model capable of classifying brain tumors 2D MRI images, and the convolutional neural network (CNN)-based model successfully achieved an accuracy of 99.21% but suffered from noticeable Overfitting. Implementing the independent tests set and early stopping mitigated this issue, making the model more reliable for production deployment and demonstrating its potential in supporting physicians in detecting brain tumors, thereby enhancing treatment efficiency. The use of Python, TensorFlow, and Keras facilitated the development of the proposed solution, focusing on a diverse set of MRI images with varying tumor sizes, locations, shapes, and intensities.
Volume: 15
Issue: 3
Page: 2337-2346
Publish at: 2026-06-01

Preservation and utilization dialogue in Indonesia’s future capital city

10.11591/ijere.v15i3.29361
Lambang Subagiyo , Nurul Fitriyah Sulaeman , Atin Nuryadin
Environmental sustainability has become crucial, especially in tropical environments that act as lungs for the world. Therefore, exploring the pro-environmental behavior (PEB) of young citizens of Eastern Borneo in Indonesia is beneficial. Exploration focused on the PEB category of students, the PEB aspect (preservation, utilization, appreciation), and student responses to the local environmental issues. This study surveyed 651 9th-grade students (15-year-olds) in six cities around Eastern Borneo. The measurement of PEB was carried out using the adapted two major environmental values model with an added scale for appreciation. Additional open-ended questions were applied to clarify the students’ perspectives on the significant environmental issues in Eastern Borneo. The result showed that only half of the students (51.31%) had advanced PEB, with the rest classified as transitional (48.23%) and naive (0.46%). Among the three PEB aspects, utilization scored the highest, indicating that the students were strongly inclined to endorse the importance of environmental utilization for human welfare. Moreover, the majority favored relocating the capital city, which highlights the importance of a new capital city owing to the overcrowded state of the current capital city (Jakarta) and the decentralization of the development of Indonesia. Nevertheless, it was found that they are concerned about preservation and sustainability regarding coal mining and palm plantations. Therefore, it was considered that environmental education for students needs enhancement to shape their PEB with contextual environmental issues.
Volume: 15
Issue: 3
Page: 2011-2020
Publish at: 2026-06-01

Bug safari: promoting ecological awareness in early childhood through nature-based learning

10.11591/ijere.v15i3.38526
Kazım Biber , Caner Börekci
This study examines the effectiveness of a nature-based educational program called bug safari, designed to enhance preschool children’s attitudes toward small creatures, particularly bugs, and to foster their ecological awareness. Developed within the framework of the Reggio Emilia approach, the program integrates multi-sensory and interdisciplinary learning methods, including observation, drama, storytelling, art activities, and parental involvement. The study was conducted in two preschool classrooms in Balıkesir, Türkiye. In the experimental group, bug safari activities were implemented once a week for six weeks, while the control group continued with the existing preschool curriculum. Data were collected using the 22-item bug awareness and ecological awareness questionnaire, developed by the researcher, and administered as both a pre-test and post-test. A mixed-design analysis of variance (ANOVA) revealed that the experimental group showed statistically significant improvements in bug awareness, understanding of the role of bugs in the ecosystem, and ecological consciousness, whereas no significant changes were observed in the control group. The findings indicated that nature-based programs involving direct experiences and active participation effectively promoted positive environmental attitudes and ecological awareness in early childhood. This study underscores the importance of integrating child centered, experiential, and nature-oriented approaches into preschool education to support cognitive, emotional, and behavioral development.
Volume: 15
Issue: 3
Page: 2217-2227
Publish at: 2026-06-01

Practices and strategies of informal assessments on grammar rules among second language learners

10.11591/ijere.v15i3.37717
Jason V. Chavez , Rolly G. Salveleon , Ma. Theresa L. Eustaquio , Haydee G. Adalia , Ma. Pilar T. Rosaldo , Joseph B. Quinto , Salita D. Dimzon , Sar-Ana M. Abdurasul , Rasmil T. Abdurasul , Ivy M. Nazareth
While informal assessment offers authentic insights into second language (L2) grammar acquisition, the specific strategies and implementation challenges remain underexplored. This study investigated the practices employed by L2 educators in conducting informal grammar assessments and the obstacles they encounter. Using a qualitative exploratory design, 20 purposively selected language educators from diverse linguistic regions in the Philippines participated in semi-structured interviews. Data were analyzed using reflexive thematic analysis. The findings revealed a pedagogical shift from static testing to stealth monitoring, characterized by contextualized micro-checks, gamified strategies to lower affective filters, and peer-scaffolded evaluation. However, significant challenges emerged, specifically the tension between assessment validity and reliability, as well as cognitive overload due to the dual burden of instruction and real-time data recording. The study concluded that while educators prioritize the authenticity of low-stakes assessment, effective implementation requires enhanced assessment literacy and structural support to mitigate subjectivity and operational fatigue.
Volume: 15
Issue: 3
Page: 2379-2389
Publish at: 2026-06-01

Analytic algebraic Riccati solution for a robust control system: application to 2-DOF arm robot

10.11591/ijece.v16i3.pp1159-1174
Menad Meriem , Ahmed Foitih Zoubir , Mokhtari Abdellah
An analytic solution to the Riccati algebraic equation has been investigated by employing eigenvalue–eigenvector techniques combined with the Gram–Schmidt orthogonality process. An analytic solution to the Riccati algebraic equation has been investigated by employing eigenvalue–eigenvector techniques combined with the Gram–Schmidt orthogonalization process. The applied method is used to improve robust control of second and third-order state-dependent systems by handling nonlinearities. An H∞ controller is designed in this context via backstepping technique to enhance robustness and reduce computational effort. The effectiveness of this method has been demonstrated on a two-degree-of-freedom (2-DOF) robotic manipulator arm. Simulation results validate the performance of the controller, showing improved tracking accuracy, disturbance rejection, and overall system stability, thereby confirming the efficiency and applicability of the combined analytic Riccati algebraic equation and H∞ backstepping approach for nonlinear robotic systems.
Volume: 16
Issue: 3
Page: 1159-1174
Publish at: 2026-06-01

AI-assisted speaking instruction and English as a foreign language learners’ oral accuracy and fluency: a quasi-experimental study

10.11591/ijere.v15i3.38907
Xiaolin Wang , Malini Ganapathy
This study investigated the effects of artificial intelligence (AI)-assisted speaking instruction using a generative AI (GenAI) chatbot on Chinese vocational college English as a foreign language (EFL) learners’ oral accuracy and fluency. A quasi-experimental pretest-posttest control group design was adopted with 80 students. The experimental group engaged in AI-mediated speaking activities, while the control group received conventional instruction. Oral performance was assessed using analytic rubrics adapted from international English language testing system (IELTS) criteria. Results showed significant improvement in oral fluency for the experimental group, while gains in accuracy were not statistically significant. These findings suggest that GenAI chatbots provide interaction-rich environments that enhance fluency development but require complementary form-focused support to improve accuracy. Implications are discussed for integrating AI tools into vocational EFL speaking instruction.
Volume: 15
Issue: 3
Page: 2700-2707
Publish at: 2026-06-01

Expert validation of a causal model of 21st-century academic leadership in northeastern Thailand

10.11591/ijere.v15i3.39095
Dusadee Butburee , Nawee Udorn , Paitoon Puangyod
This study aimed to validate and refine a causal model of factors influencing 21st-century academic leadership among secondary school administrators in northeastern Thailand. The study addresses the growing need for an integrative leadership framework that reflects digital transformation, instructional demands, and contextual constraints in contemporary educational reform. A qualitative expert validation design was employed. A total 10 experts in educational leadership, curriculum administration, and organizational development were purposively selected to participate in semi-structured in-depth interviews. Data were analyzed using thematic content analysis and cross-expert validation to ensure conceptual clarity and contextual relevance. The findings confirmed four interrelated causal domains: leadership personality and identity; contextual and organizational support systems; proactive instructional and curriculum leadership; and innovation-oriented professional learning culture. Instructional leadership emerged as a central mediating mechanism linking internal leadership capacity and external organizational conditions to academic leadership outcomes. A refined causal model with validated indicators was synthesized, providing a theoretically grounded foundation for future instrument development and structural equation modeling (SEM). The findings offer practical and policy implications for leadership development and sustainable school improvement in rapidly changing educational environments.
Volume: 15
Issue: 3
Page: 2292-2304
Publish at: 2026-06-01

Critical literacy and curriculum reform in the digital age: a pedagogical framework for artificial intelligence-integrated education

10.11591/ijere.v15i3.36952
Pablo Agustin Artero Abellan , Maria Abellan
Artificial intelligence (AI) is reshaping education and challenging traditional curriculum models, prompting new attention to critical literacy. However, most current approaches emphasize technical proficiency while neglecting ethical, epistemological, and civic dimensions. This article addresses this gap by proposing a conceptual framework for integrating AI into curriculum design through critical pedagogy and advanced learning theory. Using a theory-driven literature review, the study synthesizes global policy frameworks and educational innovations to develop a four-part model for AI-informed critical literacy. The guiding principles include: i) interrogation of AI outputs and logics; ii) development of multiliteracies and digital semiotics; iii) promotion of democratic dialogue and participatory ethics; and iv) design of adaptive, inquiry-based learning environments. Grounded in constructivist, connectivist, and Freirean theories, the framework positions AI as a context for critical inquiry and educational transformation. The article concludes with strategies for educators and policymakers to foster equity, agency, and ethical reflection in AI-integrated learning environments, and proposes directions for future empirical research.
Volume: 15
Issue: 3
Page: 2597-2607
Publish at: 2026-06-01

A qualitative study of mathematical content knowledge and pedagogical content knowledge and self-perception in Moroccan context

10.11591/ijere.v15i3.36923
Jamal Ahmichane , Mostafa El Mallahi , Youness Hadder
Pre-service teachers’ (PSTs) tertiary training is essential to their development as competent educators and to their professional readiness. Teachers must acquire the ability to communicate mathematical material in a variety of ways. Teachers of excellence must be proficient in the relevant mathematics content knowledge (MCK) and possess a strong foundation in interacting successfully with students. This study on education has two objectives: looking into how secondary PSTs who take part in a mathematics teaching unit view themselves as they interact with and solidify their MCK, and investigating how these PSTs view and understand their “readiness” to take on such a task. 25 PSTs participating in postgraduate teacher preparation programs were given the pre-unit survey (Phase 1), whose answers were subject to an extensive analysis through a high level of evaluation using a framework assisting the researcher in identifying relationships among social phenomena, based on the similarities and differences that connect these phenomena. Self-reflections of participants revealed different levels of readiness to teach lower secondary students in mathematics. All participants emphasized the need to enhance their pedagogical content knowledge (PCK) and their MCK, and a very limited number of studied participants said they felt comfortable teaching mathematics. The study implies a significant issue with professional readiness and self-efficacy, and it recommends a need for earlier and more intensive practical experience integrated with strong mentorship. A number of implications for either policy or teacher training practice are proposed. This study will cover the main outcomes of Phase 1 in light of the body of current studies on preparing PSTs of mathematics.
Volume: 15
Issue: 3
Page: 2261-2270
Publish at: 2026-06-01

Pakistan English language policy alignment with IDLE-informed policy model

10.11591/ijere.v15i3.38739
Waqas Ahmad , Muhammad Taufiq Al Makmun
English controls academic and professional access in Pakistan, yet the National Education Policy Development Framework (NEPDF) 2024 completely ignores informal digital learning of English (IDLE), which refers to self-directed learning through digital tools: WhatsApp, YouTube, and chatbots. No prior study has examined this policy-practice gap within Pakistan’s post-2024 framework, particularly across urban and rural communities in Khyber Pakhtunkhwa, Punjab, and Sindh. This qualitative case study gathered perspectives from 20 undergraduate students, 10 teachers, and 5 policymakers through semi-structured interviews, focus groups, and content analysis of NEPDF 2024 and provincial policy texts, analyzed using NVivo-facilitated STAP thematic analysis. Findings show that students and teachers actively use IDLE tools while policymakers remain largely unaware. The IDLE-informed policy model (IIPM), grounded in connectivism, sociocultural theory (SCT), and learner autonomy, is proposed as a practical policy framework that incorporates low-bandwidth tools like WhatsApp to expand access for under-resourced learners. This study contributes to educational evaluation by assessing the alignment between Pakistan’s national language policy and grassroots IDLE practices, producing a transferable policy evaluation model for global south English as a foreign language (EFL) context.
Volume: 15
Issue: 3
Page: 2194-2204
Publish at: 2026-06-01
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