A multi-national study of reading and tracing skills in novice programmers

Lister, Raymond; Seppälä, Otto; Simon, Beth; Thomas, Lynda; Adams, Edward; Fitzgerald, Sue; Fone, William; Hamer, John; Lindholm, Morten; McCartney, Robert; Moström, Jan Erik; Sanders, Kate

doi:10.1145/1044550.1041673

Cited by 125 publications

(54 citation statements)

References 14 publications

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“…A range of activities can be used that allow students to collaborate and construct problem solutions. As an example, the following suggestions, drawing on a constructivist view of learning, are made by Van Gorp and Grissom: Reading and tracing code is also important in supporting the learning of programming (Lopez et al 2008) and being able to do this is a pre-cursor to the problemsolving skills needed to write code (Lister et al 2004). Tracing code refers to the process of stepping through a piece of code, often by hand, and noting the values of variables as the program proceeds.…”

Section: Learning To Programmentioning

confidence: 99%

Computing in the curriculum: Challenges and strategies from a teacher’s perspective

2016

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Computing is being introduced into the curriculum in many countries. Teachers' perspectives enable us to discover what challenges this presents, and also the strategies teachers claim to be using successfully in teaching the subject across primary and secondary education. The study described in this paper was carried out in the UK in 2014 where teachers were preparing for the mandatory inclusion of Computing into the curriculum. A survey was conducted of over 300 teachers who were currently teaching Computing to elicit their perspectives on challenges and strategies. From the analysis of the data, extrinsic and intrinsic challenges were identified for both teachers and students. In addition, a variety of pedagogical strategies were recommended by teachers from their own practice. In categorising approaches taken by teaching to support students five key themes emerged: unplugged type activities, contextualisation of tasks, collaborative learning, developing computational thinking, and scaffolding programming tasks. Further investigation could support whether these strategies can alleviate the challenges of teaching and learning of Computing for students and teachers. In particular developing student resilience in Computing is seen as a challenge while not many strategies are suggested. The results of this study will be useful for teachers who are new to the teaching of Computing.

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Section: Learning To Programmentioning

confidence: 99%

Computing in the curriculum: Challenges and strategies from a teacher’s perspective

2016

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“…The results of a multi-national study [4] support our view that teaching methods which emphasize memory tracing lead to greater student success: Soloway [9] claims that… skilled programmers carry out frequent "mental simulations", of both abstract designs-in-progress and code being enhanced, as a check against unwanted dynamic interactions between components of the system. He argues that such simulation strategies should be taught explicitly to students.…”

Section: Introductionmentioning

confidence: 81%

Memory Tracing

Cogan¹,

Gurwitz²

2009

J. of Computer Science

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Problem statement: Students completing introductory computing courses did not know how to program at the expected level. Seeking the underlying problem, we came to believe that students were focusing only on results and not connecting with the inner workings of their code. This left them poorly prepared to master increasingly complex problems. Approach: We hoped that by promoting memory tracing as a core competence as early as possible in introductory programming courses we would hone the understanding and skills of our students and improve their chances for succeeding in computer science. We emphasized a basic and manual approach to memory tracing--in the classroom, in conjunction with homework assignments and on exams--to help our students gain the ability to write good programs, test them and, should it become necessary, debug them. Results: Having received gratifying results from our approach in our own classes, we had moved to get the word out as quickly as possible to motivate other educators to implement it. We described how we derived benefit from memory tracing in the various contexts and we presented the details of our method for teaching students how to best use this technique. Conclusion/Recommendations: Training students early on to actively carry out a manual memory trace of programs (as opposed to relying on debuggers or print statements) will help them develop their coding skill and comfort, quite apart from any facility for finding and fixing errors. Although experienced programmers trace intuitively, beginning students do not; they need to be trained. Therefore we felt that tracing should be an explicit, emphasized component of the introductory courses.

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“…Although IT is a prominent major for undergraduate students nowadays, some IT students experience difficulties for learning IT materials, especially algorithm [8,9] and programming [10,11]. They feel that learning such materials is not a trivial task since most concepts are abstract and require high logical thinking for further understanding.…”

Section: Related Workmentioning

confidence: 99%

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

Karnalim

Ayub

2018

Int. J. Onl. Eng.

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Abstract-Educational tool is one of the prominent solutions for aiding students to learn course material in Information Technology (IT) domain. However, most of them are not used in practice since they do not properly fit student necessity. This paper evaluates the impact of an educational tool, namely PythonTutor, for completing programming laboratory task regarding data structure materials. Such evaluation will be conducted in one semester by implementing a quasi-experimental design. As a result, six findings can be deducted which are: 1) PythonTutor might positively affect student performance when the students have used such tool before; 2) Sometimes, student perspective regarding the impact of educational tool is not always in-sync with actual laboratory result; 3) the impact of PythonTutor might be improved when similar data representation is used consequently for several weeks; 4) the correlation between the use of PythonTutor and student performance might not be significant when the control and intervened group share completely different characteristics; 5) the students might experience some difficulties when they are asked to handle a big task for the first time; and 6) the students might be able to complete a particular weekly task with a promising result if the students have understood the material well.

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A multi-national study of reading and tracing skills in novice programmers

Cited by 125 publications

References 14 publications

Computing in the curriculum: Challenges and strategies from a teacher’s perspective

Computing in the curriculum: Challenges and strategies from a teacher’s perspective

Memory Tracing

A Quasi-Experimental Design to Evaluate the Use of PythonTutor on Programming Laboratory Session

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