Experience report: identifying unexpected programming misconceptions with a computer systems approach

Fionnuala Johnson; Stephen Mcquistin; John O'donnell; Quintin Cutts

doi:10.1145/3502718.3524775

Experience report: identifying unexpected programming misconceptions with a computer systems approach

Fionnuala Johnson, Stephen Mcquistin, John O'donnell, Quintin Cutts

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

An increasing number of students arrive at university with programming experience and pre-formed mental models. These models are often incorrect, with students holding entrenched misconceptions. In this paper, we describe a study that investigated whether making explicit connections between our introductory Python programming and computing systems courses could expose mental models and help identify and fix misconceptions. We hypothesised that students would develop a correct mental model by creating a low level systems implementation of a high level program. While we identified misconceptions, these prevented the students from making explicit links and correcting their mental models. We detail these misconceptions, develop a set of hypotheses for why these were held, and suggest future studies.

Original language	English
Title of host publication	Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022)
Place of Publication	New York, NY
Publisher	ACM
Pages	325-330
Number of pages	6
ISBN (Electronic)	9781450392013
DOIs	https://doi.org/10.1145/3502718.3524775
Publication status	Published - 7 Jul 2022
Event	27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022 - Dublin, Ireland Duration: 8 Jul 2022 → 13 Jul 2022 Conference number: 27 https://iticse.acm.org/2022/papers/

Publication series

Name	Annual conference on innovation and technology in computer science education, ITiCSE
Volume	1
ISSN (Print)	1942-647X

Conference

Conference	27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022
Abbreviated title	ITiCSE 2022
Country/Territory	Ireland
City	Dublin
Period	8/07/22 → 13/07/22
Internet address	https://iticse.acm.org/2022/papers/

Keywords

Introductory programming
Mental models
Misconceptions

Access to Document

10.1145/3502718.3524775

https://eprints.gla.ac.uk/267388/

Cite this

Johnson, F., Mcquistin, S., O'donnell, J., & Cutts, Q. (2022). Experience report: identifying unexpected programming misconceptions with a computer systems approach. In Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022) (pp. 325-330). (Annual conference on innovation and technology in computer science education, ITiCSE; Vol. 1). ACM. https://doi.org/10.1145/3502718.3524775

Johnson, Fionnuala ; Mcquistin, Stephen ; O'donnell, John et al. / Experience report : identifying unexpected programming misconceptions with a computer systems approach. Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022). New York, NY : ACM, 2022. pp. 325-330 (Annual conference on innovation and technology in computer science education, ITiCSE).

@inproceedings{af4d6f21e0964bf69abc0d1860e03e29,

title = "Experience report: identifying unexpected programming misconceptions with a computer systems approach",

abstract = "An increasing number of students arrive at university with programming experience and pre-formed mental models. These models are often incorrect, with students holding entrenched misconceptions. In this paper, we describe a study that investigated whether making explicit connections between our introductory Python programming and computing systems courses could expose mental models and help identify and fix misconceptions. We hypothesised that students would develop a correct mental model by creating a low level systems implementation of a high level program. While we identified misconceptions, these prevented the students from making explicit links and correcting their mental models. We detail these misconceptions, develop a set of hypotheses for why these were held, and suggest future studies.",

keywords = "Introductory programming, Mental models, Misconceptions",

author = "Fionnuala Johnson and Stephen Mcquistin and John O'donnell and Quintin Cutts",

year = "2022",

month = jul,

day = "7",

doi = "10.1145/3502718.3524775",

language = "English",

series = "Annual conference on innovation and technology in computer science education, ITiCSE",

publisher = "ACM",

pages = "325--330",

booktitle = "Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022)",

address = "United States",

note = "27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022, ITiCSE 2022 ; Conference date: 08-07-2022 Through 13-07-2022",

url = "https://iticse.acm.org/2022/papers/",

}

Johnson, F, Mcquistin, S, O'donnell, J & Cutts, Q 2022, Experience report: identifying unexpected programming misconceptions with a computer systems approach. in Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022). Annual conference on innovation and technology in computer science education, ITiCSE, vol. 1, ACM, New York, NY, pp. 325-330, 27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022, Dublin, Ireland, 8/07/22. https://doi.org/10.1145/3502718.3524775

Experience report: identifying unexpected programming misconceptions with a computer systems approach. / Johnson, Fionnuala; Mcquistin, Stephen; O'donnell, John et al.
Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022). New York, NY: ACM, 2022. p. 325-330 (Annual conference on innovation and technology in computer science education, ITiCSE; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Experience report

T2 - 27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022

AU - Johnson, Fionnuala

AU - Mcquistin, Stephen

AU - O'donnell, John

AU - Cutts, Quintin

N1 - Conference code: 27

PY - 2022/7/7

Y1 - 2022/7/7

N2 - An increasing number of students arrive at university with programming experience and pre-formed mental models. These models are often incorrect, with students holding entrenched misconceptions. In this paper, we describe a study that investigated whether making explicit connections between our introductory Python programming and computing systems courses could expose mental models and help identify and fix misconceptions. We hypothesised that students would develop a correct mental model by creating a low level systems implementation of a high level program. While we identified misconceptions, these prevented the students from making explicit links and correcting their mental models. We detail these misconceptions, develop a set of hypotheses for why these were held, and suggest future studies.

AB - An increasing number of students arrive at university with programming experience and pre-formed mental models. These models are often incorrect, with students holding entrenched misconceptions. In this paper, we describe a study that investigated whether making explicit connections between our introductory Python programming and computing systems courses could expose mental models and help identify and fix misconceptions. We hypothesised that students would develop a correct mental model by creating a low level systems implementation of a high level program. While we identified misconceptions, these prevented the students from making explicit links and correcting their mental models. We detail these misconceptions, develop a set of hypotheses for why these were held, and suggest future studies.

KW - Introductory programming

KW - Mental models

KW - Misconceptions

U2 - 10.1145/3502718.3524775

DO - 10.1145/3502718.3524775

M3 - Conference contribution

AN - SCOPUS:85134434353

T3 - Annual conference on innovation and technology in computer science education, ITiCSE

SP - 325

EP - 330

BT - Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022)

PB - ACM

CY - New York, NY

Y2 - 8 July 2022 through 13 July 2022

ER -

Johnson F, Mcquistin S, O'donnell J, Cutts Q. Experience report: identifying unexpected programming misconceptions with a computer systems approach. In Proceedings of the 27th ACM conference on innovation and technology in computer science education (ITiCSE 2022). New York, NY: ACM. 2022. p. 325-330. (Annual conference on innovation and technology in computer science education, ITiCSE). doi: 10.1145/3502718.3524775

Experience report: identifying unexpected programming misconceptions with a computer systems approach

Abstract

Publication series

Conference

Keywords

Access to Document

Fingerprint

Cite this