Ndrumi : Jurnal Ilmu Pendidikan dan Humaniora

UNDERSTANDING EFL STUDENTS' DEPENDENCY ON CHATGPT IN ENGLISH LANGUAGE LEARNING: EVIDENCE FROM INDONESIAN HIGHER EDUCATION

Epos Sister Krismon Selan Dakhi — 2025-06-07

This study investigates the growing dependency of Indonesian EFL students on ChatGPT in the context of English language learning. Using a qualitative descriptive design, data were gathered from learning journals and semi-structured interviews involving nine undergraduate students across three universities. Thematic analysis revealed that students widely perceived ChatGPT as a valuable tool for enhancing writing, vocabulary, and confidence. However, its frequent use led to behavioral and emotional dependency. Factors contributing to this dependency included ease of access, low linguistic self-efficacy, academic pressure, and perceived AI authority. Notably, dependency correlated with reduced engagement in traditional learning strategies, diminished critical thinking, and limited learner autonomy. While ChatGPT offers substantial educational benefits, its overuse raises concerns about passive learning and cognitive disengagement. The findings highlight the need for pedagogical strategies that foster critical AI literacy and promote balanced use. This study contributes to the growing discourse on ethical and effective AI integration in language education

THE APPLICATION OF HOMBO BATU LOCAL WISDOM-BASED LEARNING IN ENHANCING STUDENT DISCIPLINE AND COOPERATION IN THE NIAS ISLANDS

Darmawan Harefa — 2025-06-07

This study aims to analyze the implementation of Hombo Batu local wisdom-based learning in improving student discipline and cooperation in the Nias Islands. Hombo Batu is a local cultural tradition that contains values of cooperation, discipline, and responsibility, which are integrated into learning activities in schools to strengthen students' character. This research employs a qualitative approach with a case study design conducted in several primary and secondary schools in the Nias Islands. Data were collected through observation, interviews, and document analysis related to the implementation of Hombo Batu activities in the learning process. The results show that the application of Hombo Batu-based learning is effective in improving student discipline, as reflected in time management, responsibility for tasks, and adherence to rules. Additionally, student cooperation also increased, demonstrated by better collaboration in group tasks and joint activities. This learning approach also had a positive impact on strengthening students' local cultural identity. This study suggests that local wisdom-based learning, such as Hombo Batu, should be further expanded and integrated into the educational curriculum in other regions, with attention to infrastructure and teacher training.

EXPLORING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON FOREIGN LANGUAGE ANXIETY IN LANGUAGE LEARNING (INDONESIA AND ENGLISH)

Abdul Hamid Aly — 2025-06-14

This study explores the impact of Artificial Intelligence (AI) on Foreign Language Anxiety (FLA) among university students (Indonesia and English study Programs). Using a qualitative phenomenological approach, data were collected from 300 students across multiple institutions in the Jabodetabek region. The study examines how AI tools, such as chatbots and adaptive learning platforms, influence students' anxiety levels during foreign language learning. Key findings indicate that AI reduces FLA by providing personalized learning experiences, real-time feedback, and low-pressure environments for language practice. However, some students reported increased anxiety due to the perceived constant monitoring and the lack of human interaction. The study concludes that while AI offers significant benefits in reducing anxiety, it also introduces new forms of stress, particularly related to technological engagement. This paper contributes to the existing literature by addressing the emotional dimensions of AI integration in language education, providing insights for educators on how to balance AI tools with human interaction to maximize the learning experience. Future research should focus on developing AI tools that integrate emotional support alongside cognitive feedback to further mitigate FLA.

MEMANFAATKAN TEORI BELAJAR BEHAVIORISME UNTUK MEMPERKUAT PEMBELAJARAN DEEP LEARNING

Chandra Saptanto Juraganda S, — 2025-07-24

This study aims to examine the utilization of behaviorist learning theory to strengthen deep learning instruction through a systematic literature review approach. Deep learning, as a branch of artificial intelligence, demands high-level conceptual understanding and technical skills. Meanwhile, behaviorist theory offers structured learning principles—such as reinforcement, stimulus-response, and repetition—that are relevant for building disciplined and goal-oriented learning processes. A review of scientific literature from 2020 to 2025 indicates that the application of behaviorist principles can enhance student motivation, concept retention, and technical proficiency in mastering deep learning materials. Positive reinforcement and immediate feedback have been shown to effectively reinforce desired learning behaviors, while systematic repetition improves long-term retention and problem-solving abilities. Furthermore, integrating behaviorist principles into digital learning systems increases the effectiveness of adaptive and self-directed learning. Nevertheless, behaviorism should be combined with cognitive and constructivist approaches to achieve more comprehensive learning outcomes. This study recommends the strategic use of behaviorism as a foundational framework in the design of deep learning instruction in higher education settings.