What, where, when and how: Finnish children’s perceptions of learning in preschool

Mertala, Pekka

doi:10.1080/03004430.2021.1970546

Cited by 4 publications

(2 citation statements)

References 28 publications

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“…Individuals often hold colloquial conceptions of learning that diverge from scholarly definitions. Children, for instance, conceptualize learning as the acquisition of skills, knowledge, or understanding (Mertala, 2022;Pramling, 1998;Sandberg et al, 2017). An interesting consideration is how these varying conceptions of learning align with the principles and current boundaries of machine learning.…”

Section: Conceptual Notions On Machine(s And) Learningmentioning

confidence: 99%

Finnish primary school students’ conceptions of machine learning

Mertala,

Fagerlund,

Lehtoranta

et al. 2024

Preprint

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Background and context Language is a powerful tool in shaping thought about abstract domains, including the realm of computing and digital technologies. Review of research on children's machine learning (ML) conceptions suggests that participating children were often provided with conceptual clues about the principles of ML before being asked about their conceptions (i.e., asking them how one could teach a computer). Since the term ML is not explicit about who is learning and from whom, this procedure has arguably steered their answers: with less nudging instruction, ML could also be understood as a process in which a human uses a machine, a computer, for instance, for learning purposes.ObjectiveThis study investigates what kind of conceptions primary school students have about ML if they are not conceptually "primed" with the idea that in ML, humans teach computers.MethodQualitative survey responses from 197 Finnish primary schoolers were analyzed via an abductive method.FindingsWe identified three partly overlapping ML conception categories, starting from the most accurate one: ML is about teaching machines (34%), ML is about coding (7.6%), and ML is about learning via or about machines (37.1%).ImplicationsThe findings suggest that without conceptual clues, children's conceptions of ML are varied and may include misconceptions such as ML is about learning via or about machines. The findings underline the importance of clear and systematic use of key concepts in computer science education. Besides researchers, this study offers insights for teachers, teacher educators, curriculum developers, and policymakers.

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Section: Conceptual Notions On Machine(s And) Learningmentioning

confidence: 99%

Finnish primary school students’ conceptions of machine learning

Mertala,

Fagerlund,

Lehtoranta

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Phenomenological interviews were used to explore individuals' experiences and the meanings attributed to those experiences (Seidman, 2012) and, therefore, were an appropriate method to answer the research question. "Micro-interviews" that were short in length (Mertala, 2021) were considered an appropriate and transferable method. Originally piloted on children, this method was considered more sensitive than traditional interviews to time constraints that hamper the ability of care home staff to engage in research (Lam et al, 2018).…”

Section: Data Collectionmentioning

confidence: 99%

‘Things Won’t Improve if they’re Just Left to Fester’: A Qualitative Study Exploring How UK Care home Staff Perceive and Experience Engagement in Health Research

Stephens

Knight

2022

JLTC

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Context: Care homes are challenging environments in which to conduct research and are under-represented within research literature compared to healthcare settings. This is concerning as research can improve organisational and individual outcomes. Evidence is scant on exploring how care home staff perceive and experience research engagement; the topic requires further inquiry. Objective(s):To generate additional insights into how care home staff perceive and experience research engagement.Methods: A phenomenological approach using structured micro-interviews with a convenience, snowball sample of 26 care home staff in one care home. An inductive approach using thematic analysis was employed to analyse interview data.Findings: Most participants were unfamiliar with research, and cited time constraints, workload, and a lack of opportunity as barriers to participation. Despite their unfamiliarity, participants understood research to mean the attainment of knowledge and recognised positive and tangible outcomes as markers of successful research. Staff were generally unsure what would facilitate their engagement with research, although a few participants highlighted the role of the researcher as a determinant. Many care home staff in this study did not consider research to be part of their responsibility. Limitations:The study was limited by being based on one case study organisation, possible selection bias amongst participants, and the inability to transfer findings beyond Cornwall.Implications: More needs to be done to engage care home staff in research to improve their overall representation within research. More research is needed across different localities to replicate and validate the findings from this study.

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