Fostering Program Comprehension in Novice Programmers - Learning Activities and Learning Trajectories

This working group asserts that Program Comprehension (ProgComp) plays a critical part in the process of writing programs. For example, this paper is written from a basic draft that was edited and revised until it clearly presented our idea. Similarly, a program is written incrementally, with each step tested, debugged and extended until the program achieves its goal. Novice programmers should develop program comprehension skills as they learn to code so that they are able both to read and reason about code created by others, and to reflect on their code when writing, debugging or extending it. To foster such competencies our group identified two main goals: (g1) to collect and define learning activities that explicitly address key components of program comprehension and (g2) to define tentative theoretical learning trajectories that will guide teachers as they select and sequence those learning activities in their CS0/CS1/CS2 or K-12 courses. The WG has completed the first goal and laid down a strong foundation towards the second goal as presented in this report. After a thorough literature review, a detailed description of the Block Model is provided, as this model has been used with a dual purpose, to classify and present an extensive list of ProgComp tasks, and to describe a possible learning trajectory for a complex task, covering different cells of the Block Model matrix. The latter is intended to help instructors to decompose complex tasks and identify which aspects of ProgComp are being fostered

Introductory programming: a systematic literature review

As computing becomes a mainstream discipline embedded in the school curriculum and acts as an enabler for an increasing range of academic disciplines in higher education, the literature on introductory programming is growing. Although there have been several reviews that focus on specific aspects of introductory programming, there has been no broad overview of the literature exploring recent trends across the breadth of introductory programming. This paper is the report of an ITiCSE working group that conducted a systematic review in order to gain an overview of the introductory programming literature. Partitioning the literature into papers addressing the student, teaching, the curriculum, and assessment, we explore trends, highlight advances in knowledge over the past 15 years, and indicate possible directions for future research

Is anybody there? bootstrapping attendance with engagement

The report card for the introductory programming unit at our university has historically been unremarkable in terms of attendance rates, student success rates and student retention in both the unit and the degree course. After a course restructure recently involving a fresh approach to introducing programming, we reported a high retention in the unit, with consistently high attendance and a very low failure rate. Following those encouraging results, we collected student attendance data for several semesters and compared attendance rates to student results. We have found that interesting workshop material which directly relates to course-relevant assessment items and therefore drives the learning, in an engaging collaborative learning environment has improved attendance to an extraordinary extent, with student failure rates plummeting to the lowest in recorded history at our university

Detection of anomalies from user profiles generated from system logs

We describe research into the identification of anomalous events and event patterns as manifested in computer system logs. Prototype software has been developed with a capability that identifies anomalous events based on usage patterns or user profiles, and alerts administrators when such events are identified. To reduce the number of false positive alerts we have investigated the use of different user profile training techniques and introduce the use of abstractions to group together applications which are related. Our results suggest that the number of false alerts that are generated is significantly reduced when a growing time window is used for user profile training and when abstraction into groups of applications is used

Designing for engagement : building IT systems

Context The School of Information Technology at QUT has recently undertaken a major restructuring of their Bachelor of Information Technology (BIT) course. Some of the aims of this restructuring include a reduction in first year attrition and to provide an attractive degree course that meets both student and industry expectations. Emphasis has been placed on the first semester in the context of retaining students by introducing a set of four units that complement one another and provide introductory material on technology, programming and related skills, and generic skills that will aid the students throughout their undergraduate course and in their careers. This discussion relates to one of these four fist semester units, namely Building IT Systems. The aim of this unit is to create small Information Technology (IT) systems that use programming or scripting, databases as either standalone applications or web applications. In the prior history of teaching introductory computer programming at QUT, programming has been taught as a stand alone subject and integration of computer applications with other systems such as databases and networks was not undertaken until students had been given a thorough grounding in those topics as well. Feedback has indicated that students do not believe that working with a database requires programming skills. In fact, the teaching of the building blocks of computer applications have been compartmentalized and taught in isolation from each other. The teaching of introductory computer programming has been an industry requirement of IT degree courses as many jobs require at least some knowledge of the topic. Yet, computer programming is not a skill that all students have equal capabilities of learning (Bruce et al., 2004) and this is clearly shown by the volume of publications dedicated to this topic in the literature over a broad period of time (Eckerdal & Berglund, 2005; Mayer, 1981; Winslow, 1996). The teaching of this introductory material has been done pretty much the same way over the past thirty years. During this period of time that introductory computer programming courses have been taught at QUT, a number of different programming languages and programming paradigms have been used and different approaches to teaching and learning have been attempted in an effort to find the golden thread that would allow students to learn this complex topic. Unfortunately, computer programming is not a skill that can be learnt in one semester. Some basics can be learnt but it can take many years to master (Norvig, 2001). Faculty data typically has shown a bimodal distribution of results for students undertaking introductory programming courses with a high proportion of students receiving a high mark and a high proportion of students receiving a low or failing mark. This indicates that there are students who understand and excel with the introductory material while there is another group who struggle to understand the concepts and practices required to be able to translate a specification or problem statement into a computer program that achieves what is being requested. The consequence of a large group of students failing the introductory programming course has been a high level of attrition amongst first year students. This attrition level does not provide good continuity in student numbers in later years of the degree program and the current approach is not seen as sustainable

Analysing e-mail text authorship for forensic purposes

E-mail has become the most popular Internet application and with its rise in use has come an inevitable increase in the use of e-mail for criminal purposes. It is possible for an e-mail message to be sent anonymously or through spoofed servers. Computer forensics analysts need a tool that can be used to identify the author of such e-mail messages. This thesis describes the development of such a tool using techniques from the fields of stylometry and machine learning. An author's style can be reduced to a pattern by making measurements of various stylometric features from the text. E-mail messages also contain macro-structural features that can be measured. These features together can be used with the Support Vector Machine learning algorithm to classify or attribute authorship of e-mail messages to an author providing a suitable sample of messages is available for comparison. In an investigation, the set of authors may need to be reduced from an initial large list of possible suspects. This research has trialled authorship characterisation based on sociolinguistic cohorts, such as gender and language background, as a technique for profiling the anonymous message so that the suspect list can be reduced

A qualitative think aloud study of the early neo-Piagetian stages of reasoning in novice programmers

Recent research indicates that some of the difficulties faced by novice programmers are manifested very early in their learning. In this paper, we present data from think aloud studies that demonstrate the nature of those difficulties. In the think alouds, novices were required to complete short programming tasks which involved either hand executing ("tracing") a short piece of code, or writing a single sentence describing the purpose of the code. We interpret our think aloud data within a neo-Piagetian framework, demonstrating that some novices reason at the sensorimotor and preoperational stages, not at the higher concrete operational stage at which most instruction is implicitly targeted

Mining E-Mail Content for Author Identification Forensics

We describe an investigation into e-mail content mining for author identification, or authorship attribution, for the purpose of forensic investigation. We focus our discussion on the ability to discriminate between authors for the case of both aggregated e-mail topics as well as across different email topics. An extended set of e-mail document features including structural characteristics and linguistic patterns were derived and, together with a Support Vector Machine learning algorithm, were used for mining the e-mail content. Experiments using a number of e-mail documents generated by different authors on a set of topics gave promising results for both aggregated and multi-topic author categorisation

Language and Gender Author Cohort Analysis of e-mail for Computer Forensics

We describe an investigation of authorship gender and language background cohort attribution mining from e-mail text documents. We used an extended set of predominantly topic content-free e-mail document features such as style markers, structural characteristics and gender-preferential language features together with a Support Vector Machine learning algorithm. Experiments using a corpus of e-mail documents generated by a large number of authors of both genders gave promising results for both author gender and language background cohort categorisation

Engaging students in Programming

Poor student engagement and high failure rates in first year units were addressed at the Queensland University of Technology (QUT) with a course restructure involving a fresh approach to introducing programming. Students’ first taste of programming in the new course focused less on the language and syntax, and more on problem solving and design, and the role of programming in relation to other technologies they are likely to encounter in their studies. In effect, several technologies that have historically been compartmentalised and taught in isolation have been brought together as a breadth-first introduction to IT. Incorporating databases and Web development technologies into what used to be a purely programming unit gave students a very short introduction to each technology, with programming acting as the glue between each of them. As a result, students not only had a clearer understanding of the application of programming in the real world, but were able to determine their preference or otherwise for each of the technologies introduced, which will help them when the time comes for choosing a course major. Students engaged well in an intensely collaborative learning environment for this unit which was designed to both support the needs of students and meet industry expectations. Attrition from the unit was low, with computer laboratory practical attendance rates for the first time remaining high throughout semester, and the failure rate falling to a single figure percentage