Contemporary developments in teaching and learning introductory programming: Towards a research proposal

The teaching and learning of introductory programming in tertiary institutions is problematic. Failure rates are high and the inability of students to complete small programming tasks at the completion of introductory units is not unusual. The literature on teaching programming contains many examples of changes in teaching strategies and curricula that have been implemented in an effort to reduce failure rates. This paper analyses contemporary research into the area, and summarises developments in the teaching of introductory programming. It also focuses on areas for future research which will potentially lead to improvements in both the teaching and learning of introductory programming. A graphical representation of the issues from the literature that are covered in the document is provided in the introduction

Instructional strategies and tactics for the design of introductory computer programming courses in high school

This article offers an examination of instructional strategies and tactics for the design of introductory computer programming courses in high school. We distinguish the Expert, Spiral and Reading approach as groups of instructional strategies that mainly differ in their general design plan to control students' processing load. In order, they emphasize topdown program design, incremental learning, and program modification and amplification. In contrast, tactics are specific design plans that prescribe methods to reach desired learning outcomes under given circumstances. Based on ACT* (Anderson, 1983) and relevant research, we distinguish between declarative and procedural instruction and present six tactics which can be used both to design courses and to evaluate strategies. Three tactics for declarative instruction involve concrete computer models, programming plans and design diagrams; three tactics for procedural instruction involve worked-out examples, practice of basic cognitive skills and task variation. In our evaluation of groups of instructional strategies, the Reading approach has been found to be superior to the Expert and Spiral approaches

Plan-based delivery composition in intelligent tutoring systems for introductory computer programming

In a shell system for the generation of intelligent tutoring systems, the instructional model that one applies should be variable independent of the content of instruction. In this article, a taxonomy of content elements is presented in order to define a relatively content-independent instructional planner for introductory programming ITS's; the taxonomy is based on the concepts of programming goals and programming plans. Deliveries may be composed by the instantiation of delivery templates with the content elements. Examples from two different instructional models illustrate the flexibility of this approach. All content in the examples is taken from a course in COMAL-80 turtle graphics

A serious game for developing computational thinking and learning introductory computer programming

Owing to their ease of engagement and motivational nature, especially for younger age groups, games have been omnipresent in education since earliest times. More recently, computer video games have become widely used, particularly in secondary and tertiary education, to impart core knowledge in some subject areas and as an aid to attracting and retaining students. Academics have proposed a number of approaches, using games-based learning (GBL), to impart theoretical and applied knowledge,especially in the computer science discipline. Our research is concerned with the design of an innovative educational game framework focused on the development of Computational Thinking (CT) skills, and herein we introduce a serious game, based on our framework, which encourages the development of CT skills to facilitate learning introductory computer programming. We describe how a limited number of key introductory computer programming concepts have been mapped onto the game-play, and how an equivalent set of skills characterising CT can be acquired through playing the game. A survey response group of 25 students, following computer science and related degree programmes but with very diverse backgrounds and experience, provided initial usability feedback on the game. Their feedback confirmed that they found the game enjoyable, and also universally believed that this approach would be beneficial in helping students learn problem-solving skills for introductory computer programming. Feedback from this group will be incorporated in a revised version of the game, which will now be subject to rigorous experimental evaluation and analysis, to provide structured empirical evidence in support of our approach

From conditioning to learning communities: Implications of fifty years of research in e‐learning interaction design

This paper will consider e‐learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e‐learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné), cognitivist (Pask, Piaget and Papert), situated (Lave, Wenger and Seely‐Brown), socio‐constructivist (Vygotsky), socio‐cultural (Nardi and Engestrom) and community‐based (Wenger and Preece). Emerging from this review is the argument that effective e‐learning usually requires, or involves, high‐quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e‐learning

Facilitating Bloom\u27s Level One through Active Learning and Collaboration

Bloom\u27s taxonomy provides a means of structuring learning activities according to levels of comprehension ranging from factual knowledge to the creation of new knowledge. There are problems with presenting factual knowledge in the traditional lecture mode: student motivation, time-to-present, and course priorities. However, in Bloom\u27s taxonomy, Level 1 (factual) knowledge is the basis for knowledge comprehension at higher levels. Therefore, it is essential that the fact base comprehension be attained so that higher levels of knowledge can be addressed. Active learning and collaborative approaches have been shown to be effective in promoting learning. How can active learning and collaboration be used to overcome the problems associated with promoting Level 1 comprehension? In our introductory Computer Information Science (CIS) course, we attempt to answer this question for the topic history of computing. We have combined a student research and collaborative assignment to acquire Level 1 comprehension with a culminating College Bowl activity to reach the goal of Level 2 comprehension. In this paper we discuss course organization, course goals, the College Bowl format of quizzing, contest results, and overall observation of the process

Characterising algorithmic thinking: A university study of unplugged activities

Algorithmic thinking is a type of thinking that occurs in the context of computational thinking. Given its importance in the current educational context, it seems pertinent to deepen into its conceptual and operational understanding for teaching. The exploration of research shows us that there are almost no studies at university level where algorithmic thinking is connected to mathematical thinking, and more importantly, to characterise it and be able to analyse and evaluate it better. The aim of this research is to characterise algorithmic thinking in a university context of the Bachelor's Degree in Mathematics by unplugged tasks, offering a model of analysis through categories that establish connections between mathematical and algorithmic working spaces in three dimensions, semiotic, instrumental and discursive. The results confirm the interaction between these dimensions and their predictive value for better programming performance. The study also adds novel considerations related to the role and interaction of mathematical and computational thinking categories involved in algorithmic thinking.Instituto de Matemática Interdisciplinar (IMI)Fac. de Ciencias MatemáticasTRUEUnión EuropeaMinisterio de Ciencia e Innovaciónpu

The PTP Model: A Predictor for Computer Programming Success

The fundamental concepts of programming are essential to any Computer Science course yet, these concepts can appear significantly more abstract than students have encountered in the past. These abstract concepts can become so daunting to students, that they experience ‘programming shock’ during their first encounter with programming, as they attempt to decipher a number of concepts, error messages and unfamiliar syntax all at once. Once a student encounters programming shock, it can be extremely disheartening and if not overcome, can sometimes result in a student dropping out from a course. Through the use of specifically designed aptitude tests conducted with first year Computing students, this investigation has provided sufficient evidence to prove a link between mental model usage and student performance in an introductory programming module, as well as enabling the development of the Programming Thought Process (PTP) model, which can be used to identify students most in need of support