Sidoarjo- A professional training program on integrating Artificial Intelligence (AI) into deep learning instruction significantly strengthened the competencies of economics teachers in Sidoarjo, East Java, according to a 2026 publication in the Jurnal Pengabdian Masyarakat Formosa (JPMF). The program was conducted by Wida Wulandari, Prof. Dr. Waspodo Tjipto Subroto, Eka Hendi Andriansyah, Riza Yonisa Kurniawan, Riza Albrian Fiky Prakoso, and Muhammad Abdul Ghofur from Universitas Negeri Surabaya, together with Prattana Srisuk from Thai Global Business and Administration, Thailand. The training, implemented on May 10, 2025, demonstrated measurable improvements in teachers’ readiness to apply AI-based learning approaches in economics classrooms. The findings are important as schools increasingly adapt to digital transformation and prepare students for technology-driven economic environments.
Artificial Intelligence is rapidly reshaping education worldwide by enabling personalized learning, automated assessment systems, and adaptive instructional tools. However, many teachers still face challenges in integrating AI technologies into classroom practice. Strengthening teacher competence in AI-supported learning is therefore essential to ensure that digital transformation in education benefits both educators and students.
The training program focused on members of the Economics Subject Teacher Association (MGMP Economics) in Sidoarjo Regency. Researchers from Universitas Negeri Surabaya designed the initiative as a structured professional development activity combining face-to-face workshops with sustained online mentoring. The approach ensured that participants not only received theoretical explanations but also practiced applying AI tools directly in teaching scenarios.
Before implementation, the research team coordinated with MGMP Economics leaders to identify teachers’ needs related to AI adoption in economics education. This consultation phase helped align training materials with classroom realities. The workshop was then conducted at the Sidoarjo Regency Sports High School Auditorium, followed by continuous mentoring through a WhatsApp support group that allowed participants to continue learning after the in-person session.
Training materials introduced teachers to core AI concepts, AI-based educational platforms, and strategies for applying deep learning approaches in economics instruction. Participants practiced using digital tools to design teaching materials, support student engagement, and improve classroom interaction. The blended training format made it possible for teachers to learn without disrupting their regular teaching responsibilities.
Evaluation results confirmed strong positive responses from participants. A questionnaire completed by 57 teachers showed average scores ranging from 2.98 to 3.60 on a four-point scale across 13 assessment indicators. These scores reflect high levels of understanding, perceived usefulness, and readiness to apply AI-supported learning methods in classroom environments.
Most participants reported that the training improved their understanding of artificial intelligence concepts and introduced practical strategies for integrating AI tools into teaching activities. Teachers also highlighted the usefulness of learning how to organize lessons using AI-based educational platforms and how to apply deep learning strategies that support student-centered instruction.
According to Wida Wulandari from Universitas Negeri Surabaya, the program demonstrates that teachers are ready to adopt artificial intelligence in classroom practice when they receive structured and continuous professional support. The research team emphasized that AI technologies can enhance teaching effectiveness by enabling more adaptive and personalized learning experiences for students.
The study also identified variations in digital readiness among teachers, reflecting differences in previous technology experience and familiarity with digital learning platforms. While most participants responded positively to the training, some indicated the need for additional advanced sessions to strengthen their practical skills in applying AI more deeply in economics teaching contexts.
Despite these differences, the overall training outcomes show that combining face-to-face workshops with online mentoring creates a strong foundation for sustainable teacher development. Continuous support through digital communication platforms helped participants clarify questions quickly and maintain engagement after the training session ended.
The researchers also highlighted the broader relevance of AI integration for educational and economic development. Artificial intelligence enables educators to design learning environments that adapt to students’ individual needs and learning speeds. This flexibility supports more inclusive education and helps students develop competencies required for emerging labor markets shaped by digital innovation.
According to the Universitas Negeri Surabaya research team, integrating AI into economics education also strengthens the relationship between academic learning and real-world economic challenges. Students exposed to AI-supported learning environments gain analytical skills and technological familiarity that are increasingly essential in modern economic systems.
The training program further demonstrated that collaboration between universities and teacher professional organizations can accelerate digital transformation in schools. By providing targeted training aligned with classroom needs, higher education institutions can play a key role in strengthening teachers’ technological competence and supporting curriculum innovation.
Researchers concluded that future programs should expand project-based training formats and continue mentoring activities to ensure deeper adoption of AI-supported teaching strategies. Sustained professional development is considered essential for maximizing the long-term benefits of artificial intelligence in classroom learning environments.
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Source
“Competency Improvement: Integration of Artificial Intelligence (AI) in Deep Learning,” Jurnal Pengabdian Masyarakat Formosa (JPMF), 2026. DOI: https://doi.org/10.55927/jpmf.v5i2.147
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