Underachievement has been a longstanding focus in talent development, gifted education, and related areas of psychological and educational research. Despite high potential, many individuals do not consistently translate their abilities into academic or developmental achievement. Research has shown that underachievement does not affect all groups equally. It is particularly prevalent among learners from socioeconomically disadvantaged backgrounds, twice-exceptional individuals, and girls and women in STEM-related domains. Over more than a century of research and intervention efforts, a wide range of explanatory models and support strategies has emerged. Nevertheless, persistent gaps between potential and achievement suggest that existing approaches have achieved only limited and often uneven success. At the same time, rapid advances in digital technologies—such as learning analytics, adaptive learning systems, and intelligent tutoring environments—have begun to reshape how learning and development can be assessed and supported. The first tangible results can already be seen in efforts to combat underachievement, including structured e-mentoring, online and blended learning environments, and digitally mediated feedback systems. Advances in artificial intelligence have added new momentum to this line of work. Research on digital technologies is not being replaced, but extended and enriched by AI-driven methods. However, many open questions remain about how these approaches can be meaningfully integrated into research and practice.
The goal of this Research Topic is to explore how technology-based approaches may help address underachievement and support learning and development. Although many digital tools and interventions have been introduced in recent years, their use is often studied in isolation, with limited connections between psychological theory, technological design, and practical application. This Research Topic brings together work that examines how technological approaches relate to psychological processes such as motivation, self-regulation, feedback, and learning across time. A particular focus is on approaches that allow for continuous assessment and adaptation, rather than one-off interventions. Contributions may include studies on artificial intelligence, learning analytics, digital mentoring, or other technology-supported formats in educational and developmental contexts. Overall, the Research Topic aims to improve understanding of when and how technology-based interventions can contribute to reducing underachievement across different groups and settings.
Areas of interest include, but are not limited to the following:
• Empirical research
• Systematic Reviews
• Meta-analysis
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