Misconceptions and the Notional Machine in Very Young Programming Learners (RTP)

Lowe, Tony

doi:10.18260/1-2--30811

Cited by 3 publications

(4 citation statements)

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“…These findings echo previous studies of teaching young children to program by means of using friendly and seemingly-intuitive environments—either virtual or physical—that demonstrated how visual-spatial cues may hinder learning (Simões Gomes et al, 2018; Tony Andrew Lowe, 2018). Therefore, the obstructing mechanism may be related to visual-spatial skills, which were previously found to be positively associated with learning (Mathewson, 1999; Morrison, 2004; Salmerón & García, 2012).…”

Section: Discussionsupporting

confidence: 87%

Types of Errors in Block Programming: Driven by Learner, Learning Environment

Ben-Yaacov

Hershkovitz

2022

Journal of Educational Computing Research

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Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors—which form one of two broad categories of errors in programming, the other one being logic errors—are omitted while block programming. However, this does not mean that errors are omitted at large in such environments. In this exploratory case study of a learning environment for early programming (Kodetu), we explored errors in block programming of middle school students ( N = 123), using log files drawn from a block-based online. Analyzing 1033 failed executions, we found that errors may be driven by either learners’ knowledge and behavior, or by the learning environment design. The rate of error types was not associated with the learners’ and contextual variables examined, with the exception of task complexity (as defined by SOLO taxonomy). Our findings highlight the importance of learning from errors and of learning environment design.

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Section: Discussionsupporting

confidence: 87%

Types of Errors in Block Programming: Driven by Learner, Learning Environment

Ben-Yaacov

Hershkovitz

2022

Journal of Educational Computing Research

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“…Lowe, 2018) sought to teach children basic programming concepts by starting with rudimentary instruction and open play using a robot mouse (see Figure5.1). The researcher demonstrated the mouse's basic abilities to move forward or back and swiveling left or right, as well as how to store and clear a sequence of such commands.…”

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confidence: 99%

A Theory of Applied Mind of Programming

Lowe

2019

Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education

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exists' leading to some confusion and carefully selected language. Is the notional machine a document or tool that someone creates? Is the notional machine implied in the combination of language and hardware specifications? Is there a mechanism for validating the definition of a notional machine against reality? The vagueness of the notional machine may be the reason that "Notional machines, code tracing, mental models and program visualization are often appear conflated in the literature at least to non-experts." (Dickson, Brown, & Becker, 2020, p. 164).

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“…Du Boulay (1986) predicts that incorporating a notional machine into programming lessons can support mental model formation and help novice programmers understand how program execution occurs. Other work also advocates for direct instruction of the notional machine to support accurate mental model formation (Krishnamurthi and Fisler, 2019;Lowe, 2018;Robins, 2019;Sorva, 2013). While little work exists on how to explicitly teach the notional machine to novice programmers, there are several notable exceptions described below.…”

Section: Learning To Code Trace With Explicit and Implicit Notional M...mentioning

confidence: 99%

“…Explicit instruction about the notional machine has been proposed to support mental model formation for novice programmers (Krishnamurthi and Fisler, 2019;Lowe, 2018;Robins, 2019;Sorva, 2013). However, to date this proposal remains relatively untested.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Utility of Notional Machine Instruction in an Introductory Programming Lesson

Chiarelli¹

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Learning to program involves understanding how the computer executes programs.Code tracing is a simulation of the steps the computer takes to execute a program.The notional machine is an abstract representation of this process. Students form mental models of the notional machine when learning to code trace, but these mental models can be inaccurate or contain misconceptions. We experimentally investigated the effect on learning of using an explicit notional machine or not in a code-tracing lesson for novice programmers (N = 48). We created two versions of a tutoring system, one with a notional machine and one without, using the Cognitive Tutor Authoring Tools framework. The tutors included video lessons and self-explanation prompts to encourage participant engagement. We measured learning as the difference in scores from pretest to posttest, adjusted by prior knowledge. Learning increased overall, but there was no significant difference in learning between groups. i I would like to dedicate this thesis to my grandfather Frantisek (Frank) Fiala who was a founding faculty member of Carleton University's School of Computer Science. He has inspired my love for learning through his example and gentle encouragement, and I am so grateful for that.I would also like to thank my friends and family for constantly cheering me on, especially my mother for her enthusiasm and willingness to hear me talk for hours about the details of my research.Thank you to my committee for your time, input and ideas.Finally, thank you to Dr. Kasia Muldner for making this possible. I greatly appreciate all of the time on discussions and feedback that went into this work. Thank you for being such a kind and helpful supervisor.

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Misconceptions and the Notional Machine in Very Young Programming Learners (RTP)

Abstract: To pass the time between classes he works for Anthem as a software architect and teaches as an adjunct at CTU Online.

Cited by 3 publications

References 10 publications

Types of Errors in Block Programming: Driven by Learner, Learning Environment

Types of Errors in Block Programming: Driven by Learner, Learning Environment

A Theory of Applied Mind of Programming

Investigating the Utility of Notional Machine Instruction in an Introductory Programming Lesson

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