Influences that undermine learners' perceptions of autonomy, competence and relatedness in an online context

By Maggie Hartnett. 2015

111 citations recorded by the source corpus.

Online learning has grown considerably in recent years. However attrition rates from online courses indicate that not all learners are successful in such settings, and various factors have been identified as crucial to learner persistence. Research evidence suggests that motivation is one such factor. This study builds on previous studies by using self-determination theory (SDT) as an analytical framework to explore, in-depth, the motivation of pre-service teachers situated within an online learning context. In particular, the underlying concepts of autonomy, competence and relatedness from SDT were adopted as critical lenses to identify social and contextual influences which undermined the psychological needs of these learners. Most prominent among these in the current study were: high workload, assessment pressure, perceptions that the learning activity lacked relevance (autonomy-undermining), unclear and complicated guidelines, insufficient guidance and feedback from the instructor (competence-undermining), and communication issues with peers (relatedness-undermining). By not exclusively focusing on learners’ autonomy needs as others have done, the paper offers a more extensive picture of undermining influences on motivation than has been previously identified in online studies.

Subfields: Computer Science Applications, Developmental and Educational Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/e40af4a1f1d2d5f131f780cca5e2f05ac7fb33db

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In Computer Science Applications

In Developmental and Educational Psychology

In Social Psychology

Citations in the corpus

Applying the self-determination theory (SDT) to explain student engagement in online learning during the COVID-19 pandemic (2021, background): “…practices play an important role in fostering student motivation in online/distance learning, and teachers can accomplish this by encouraging student autonomy, by ensuring learning, and by being involved interpersonally (Hartnett, 2015; Vonderwell et al., 2007; Xie et al., 2006; Xie & Ke, 2011).”
Mobile-Based Assessment: Integrating acceptance and motivational factors into a combined model of Self-Determination Theory and Technology Acceptance (2017, methodology): “Ubiquity, context-sensitivity, technology support, time and location independence (PUV), meaningful feedback (F), relevant and optimally challenging educational content and tasks (C), self-efficacy (MSE), communication and interactions among peers and between peers and teacher (COL, INT) are all det”
Digital support for student engagement in blended learning based on self-determination theory (2021, background): “…digital support design (i) offers various learning resources with descriptions that indicate their relevance to students (Bedenlier et al., 2020; Hartnett, 2015), (ii) provides scaffolding exercises, such as level-up exercises, that help students build their confidence and knowledge to tackle…”
Using personalized learning as an instructional approach to motivate learners in online higher education: Learner self-determination and intrinsic motivation (2020, background): “Similarly, Hartnett (2015) found that when students were grouped into small discussion groups, such as in the personalized learning course in our study, the students lacked for interaction because the students tended to only interact with students who might work within their small groups.”
The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney (2023, unknown): “This is aligned with most of SDT-based students on digital education (Chiu, 2021, 2022; Hartnett, 2015; Trenshaw et al., 2016).”