Annotated Bibliography On Self-Efficacy In MLearning ✓ Solved

Annotated Bibliography Self Efficacy In M Learningrunning Head 7ann

Annotated Bibliography Self Efficacy In M Learningrunning Head 7ann

Analyze the role of self-efficacy in mobile learning (m-learning) through a review of academic literature, focusing on how self-efficacy influences technology acceptance, engagement, motivation, and academic achievement within mobile and digital learning environments.

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Introduction

The rapid advancement of mobile technology has transformed the landscape of modern education, leading to increased interest in understanding the psychological factors that influence its effectiveness. Among these factors, self-efficacy—an individual's belief in their capability to perform tasks—has garnered significant attention for its role in promoting engagement, motivation, and academic success in mobile learning (m-learning) contexts. This paper critically examines the existing scholarly literature to elucidate how self-efficacy impacts m-learning, particularly in relation to technology acceptance, learner persistence, and achievement.

Self-Efficacy and Technology Acceptance

Self-efficacy is integral to technology acceptance, impacting students’ willingness to engage with new digital tools. Almeida and colleagues (2012) argue that perceived self-efficacy influences students’ intentions to adopt and utilize e-learning platforms effectively. Similarly, Alenezi et al. (2010) utilize the Technology Acceptance Model (TAM) and demonstrate that self-efficacy significantly predicts students' intention to engage with e-learning environments. These findings suggest that fostering self-efficacy can serve as a strategic approach to enhancing technology adoption, especially in mobile learning where user confidence directly correlates with engagement levels.

Development and Measurement of Self-Efficacy in M-Learning

Understanding how self-efficacy can be developed and accurately measured is vital in designing effective m-learning interventions. Al-Awidi and Alghazo (2012) conducted an empirical study within a teacher education context in the UAE, revealing that authentic teaching experiences notably improve preservice teachers’ self-efficacy for technology integration. Concurrently, Artino (2012) emphasizes that instructional design grounded in self-efficacy principles can enhance learner outcomes. Additionally, Chen and Usher (2013) explore various sources of self-efficacy, such as mastery experiences and social persuasion, which are particularly relevant for mobile learners seeking confidence in their digital skills. Effective measurement tools that capture these dimensions are fundamental to tailoring interventions that bolster self-efficacy in m-learning environments.

Role of Self-Efficacy in Engagement, Persistence, and Motivation

Empirical research consistently demonstrates that self-efficacy influences learners’ motivation and persistence in digital contexts. Gao et al. (2011) found a positive association between self-efficacy and motivation for physical activity, reinforcing the idea that belief in one's abilities encourages sustained effort in self-directed learning tasks. In the domain of academic achievement, Tella, Tella, and Adeniyi (2011) established a significant relationship between self-efficacy and academic performance in secondary school students, emphasizing its role as a catalyst for persistence and success. These findings are pertinent for m-learning, where learner autonomy and motivation are often challenged by technological unfamiliarity or anxiety.

Self-Efficacy and Engagement in Digital and Mobile Contexts

Beyond academic settings, self-efficacy influences engagement with digital games and mobile applications. Hong et al. (2012) demonstrated that high self-efficacy enhances flow states—a psychological condition characterized by deep immersion—during gaming, suggesting similar mechanisms operate in educational apps. Moreover, Irby and Strong (2013) found that agricultural students’ self-efficacy positively predicted their acceptance of mobile technology in classroom settings. These insights imply that boosting self-efficacy can mitigate anxiety and resistance to mobile tools, thereby fostering deeper engagement and effective use of mobile resources for learning.

Implications for Designing M-Learning Strategies

Informed by these studies, educators and developers should prioritize strategies that enhance self-efficacy, such as scaffolded instruction, feedback, and opportunities for mastery experiences. Bandura’s (1986, 1991) foundational work on self-efficacy underscores the importance of mastery experiences and social modeling in cultivating learner confidence. Integrating these principles into mobile learning applications, for example, through personalized feedback and peer support, can facilitate greater learner autonomy and persistence. Furthermore, Tella et al. (2011) emphasize the importance of addressing individual differences like locus of control to tailor interventions effectively.

Conclusion

The review of literature substantiates the pivotal role of self-efficacy in promoting successful m-learning experiences. Its influence extends across technology acceptance, engagement, persistence, and academic achievement, highlighting the need for intentional strategies to develop learner confidence in digital environments. As mobile learning continues to evolve, further research should examine innovative methods to enhance self-efficacy, ensuring that digital education remains accessible and effective for diverse learner populations.

References

  • Almeida, L., Hsu, P.-L., & Jones, R. (2012). Factors influencing students’ technology acceptance in higher education. Journal of Educational Technology & Society, 15(2), 134-146.
  • Al-Awidi, H., & Alghazo, I. (2012). The effect of student teaching experience on preservice elementary teachers’ self-efficacy beliefs for technology integration in the UAE. Educational Technology Research and Development, 60(5), 923–941.
  • Artino, A. (2012). Academic self-efficacy: From educational theory to instructional practice. Perspectives on Medical Education, 1(2), 76–85.
  • Bandura, A. (1986). Social Foundations of Thought and Action: A Socially Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall.
  • Bandura, A. (1993). Perceived self-efficacy in cognitive development and functioning. Educational Psychologist, 28(2), 117–148.
  • Chen, J., & Usher, E. (2013). Profiles of the sources of science self-efficacy. Learning and Individual Differences, 24, 11–21.
  • Gao, Z., Lee, A. M., Xiang, P., & Kosma, M. (2011). Effect of learning activity on students’ motivation, physical activity levels and effort/persistence. ICHPER-SD Journal of Research, 6(1), 27–33.
  • Hong, J.-C., Pei-Yu, C., Shih, H.-F., Lin, P.-S., & Hong, J.-C. (2012). Computer self-efficacy, competitive anxiety and flow state: Escaping from firing online game. Turkish Online Journal of Educational Technology, 11(3), 70–76.
  • Irby, T. L., & Strong, R. (2013). Agricultural education students’ acceptance and self-efficacy of mobile technology in classrooms. NACTA Journal, 57(1), 82–87.
  • Tella, A., Tella, A., & Adeniyi, S. O. (2011). Locus of control, interest in schooling and self-efficacy as predictors of academic achievement among junior secondary school students in Osun State, Nigeria. New Horizons in Education, 59(1), 25–37.

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