Another breadth-first approach to CS I using python

Shannon, Christine

doi:10.1145/611977.611980

Cited by 7 publications

(7 citation statements)

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“…Therefore simpler language might enable the students to see the benefits of programming earlier and thus increase the motivation. Based on the literature (for example, [15,19,14 Finally, it pays off to bring forward that the students can use the programming knowledge also indirectly during their career. For example, one might need to co-operate with software engineers during their career, when one is working in a customer role.…”

Section: Discussionmentioning

confidence: 99%

CS minors in a CS1 course

Kinnunen¹,

Malmi²

2008

Proceedings of the Fourth International Workshop on Computing Education Research

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The focus of this paper is on science students (CS minors) in a CS1 Java course at a technical university. The following three questions are discussed: 1) Which programming related topics the students at the target CS1 course find difficult to learn, and what is the difference between the students that passed the course and the students that dropped out of the course. 2) What kind of strategies both the passed and the dropout students used when they faced a difficult programming related topic. 3) Why some students decided to drop out of the course.The research questions are tackled with a quantitative approach. 459 students that passed the CS1 course and 119 dropout students answered the questionnaire. The most difficult topics to learn were finding runtime errors and planning one's own code. Inheritance & abstract classes, and handling files were also regarded as difficult topics. The open-ended question in the questionnaire revealed six viable strategies the students used when they faced difficult topics. The factor analysis elicited five dropout reasons: course arrangements, difficulty to understand course topics, time management and preferences, lack of consequences of dropping out, and effect of other courses.The results are discussed in the light of the general system theory that highlights the multi-dimensionality of the dropout phenomenon.

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Section: Discussionmentioning

confidence: 99%

CS minors in a CS1 course

Kinnunen¹,

Malmi²

2008

Proceedings of the Fourth International Workshop on Computing Education Research

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“…The results of a survey administered to students who made use of the study pack revealed positive perceptions of Python as a programming language. Along the same lines, empirical studies by Patterson-McNeill [2006], Stamey and Sheel [2010], Miller and Ranum [2005], Oldham [2005], Goldwasser and Letscher [2008] and Shannon [2003] detail the choices involved in redesigning the curriculum and the shift from one language to another in their colleges and argue for dramatic improvements with the use of Python, but no explicit evaluation results are reported in any of these studies.…”

Section: Literature Reviewmentioning

confidence: 99%

Teaching Introductory Programming

Koulouri

Lauria

Macredie

2014

ACM Trans. Comput. Educ.

105

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Teaching programming to beginners is a complex task. In this paper, the effects of three factors -choice of programming language, problem-solving training and the use of formative assessment -on learning to program were investigated. The study adopted an iterative methodological approach carried out across four consecutive years. To evaluate the effects of each factor (implemented as a single change in each iteration) on students' learning performance, the study used quantitative, objective metrics. The findings revealed that using a syntactically-simple language (Python) instead of a more complex one (Java) facilitated students' learning of programming concepts. Moreover, teaching problem-solving before programming yielded significant improvements in students' performance. These two factors were found to have variable effects on the acquisition of basic programming concepts. Finally, it was observed that effective formative feedback in the context of introductory programming depends on multiple parameters. The paper discusses the implications of these findings, identifies avenues for further research and argues for the importance of studies in computer science education anchored on sound research methodologies to produce generalizable results.

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“…Python comes with an extensive standard library, including tools for graphical programming and numerical processing, which means it can be used for a wide range of non-trivial applications. Python is ideal in a context serving newcomers and experienced programmers (Shannon, 2003).…”

Section: Pythonmentioning

confidence: 99%

Multidisciplinary instruction with the Natural Language Toolkit

Bird

Klein

Loper

et al. 2008

Proceedings of the Third Workshop on Issues in Teaching Computational Linguistics - TeachCL '08

339

210

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The Natural Language Toolkit (NLTK) is widely used for teaching natural language processing to students majoring in linguistics or computer science. This paper describes the design of NLTK, and reports on how it has been used effectively in classes that involve different mixes of linguistics and computer science students. We focus on three key issues: getting started with a course, delivering interactive demonstrations in the classroom, and organizing assignments and projects. In each case, we report on practical experience and make recommendations on how to use NLTK to maximum effect.

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Another breadth-first approach to CS I using python

Cited by 7 publications

References 0 publications

CS minors in a CS1 course

CS minors in a CS1 course

Teaching Introductory Programming

Multidisciplinary instruction with the Natural Language Toolkit

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