A Human-Centric System for Symbolic Reasoning About Code

While testing and tracing on specific input values are useful starting points for students to understand program behavior, ultimately students need to be able to reason rigorously and logically about the correctness of their code on all inputs without having to run the code. Symbolic reasoning is reasoning abstractly about code using arbitrary symbolic input values, as opposed to specific concrete inputs. The overarching goal of this research is to help students learn symbolic reasoning, beginning with code containing simple assertions as a foundation and proceeding to code involving data abstractions and loop invariants. Toward achieving this goal, this research has employed multiple experiments across five years at three institutions: a large, public university, an HBCU (Historically Black Colleges and Universities), and an HSI (Hispanic Serving Institution). A total of 862 students participated across all variations of the study. Interactive, online tools can enhance student learning because they can provide targeted help that would be prohibitively expensive without automation. The research experiments employ two such symbolic reasoning tools that had been developed earlier and a newly designed human-centric reasoning system (HCRS). The HCRS is a first step in building a generalized tutor that achieves a level of resolution necessary to identify difficulties and suggest appropriate interventions. The experiments show the value of tools in pinpointing and classifying difficulties in learning symbolic reasoning, as well as in learning design-by-contract assertions and applying them to develop loop invariants for code involving objects. Statistically significant results include the following. Students are able to learn symbolic reasoning with the aid of instruction and an online tool. Motivation improves student perception and attitude towards symbolic reasoning. Tool usage improves student performance on symbolic reasoning, their explanations of the larger purpose of code segments, and self-efficacy for all subpopulations

A Novel ILP Framework for Summarizing Content with High Lexical Variety

Summarizing content contributed by individuals can be challenging, because people make different lexical choices even when describing the same events. However, there remains a significant need to summarize such content. Examples include the student responses to post-class reflective questions, product reviews, and news articles published by different news agencies related to the same events. High lexical diversity of these documents hinders the system's ability to effectively identify salient content and reduce summary redundancy. In this paper, we overcome this issue by introducing an integer linear programming-based summarization framework. It incorporates a low-rank approximation to the sentence-word co-occurrence matrix to intrinsically group semantically-similar lexical items. We conduct extensive experiments on datasets of student responses, product reviews, and news documents. Our approach compares favorably to a number of extractive baselines as well as a neural abstractive summarization system. The paper finally sheds light on when and why the proposed framework is effective at summarizing content with high lexical variety.Comment: Accepted for publication in the journal of Natural Language Engineering, 201

A study of novice programmer performance and programming pedagogy.

Identifying and mitigating the difficulties experienced by novice programmers is an active area of research that has embraced a number of research areas. The aim of this research was to perform a holistic study into the causes of poor performance in novice programmers and to develop teaching approaches to mitigate them. A grounded action methodology was adopted to enable the primary concepts of programming cognitive psychology and their relationships to be established, in a systematic and formal manner. To further investigate novice programmer behaviour, two sub-studies were conducted into programming performance and ability. The first sub-study was a novel application of the FP-Tree algorithm to determine if novice programmers demonstrated predictable patterns of behaviour. This was the first study to data mine programming behavioural characteristics rather than the learner’s background information such as age and gender. Using the algorithm, patterns of behaviour were generated and associated with the students’ ability. No patterns of behaviour were identified and it was not possible to predict student results using this method. This suggests that novice programmers demonstrate no set patterns of programming behaviour that can be used determine their ability, although problem solving was found to be an important characteristic. Therefore, there was no evidence that performance could be improved by adopting pedagogies to promote simple changes in programming behaviour beyond the provision of specific problem solving instruction. A second sub-study was conducted using Raven’s Matrices which determined that cognitive psychology, specifically working memory, played an important role in novice programmer ability. The implication was that programming pedagogies must take into consideration the cognitive psychology of programming and the cognitive load imposed on learners. Abstracted Construct Instruction was developed based on these findings and forms a new pedagogy for teaching programming that promotes the recall of abstract patterns while reducing the cognitive demands associated with developing code. Cognitive load is determined by the student’s ability to ignore irrelevant surface features of the written problem and to cross-reference between the problem domain and their mental program model. The former is dealt with by producing tersely written exercises to eliminate distractors, while for the latter the teaching of problem solving should be delayed until the student’s program model is formed. While this does delay the development of problem solving skills, the problem solving abilities of students taught using this pedagogy were found to be comparable with students taught using a more traditional approach. Furthermore, monitoring students’ understanding of these patterns enabled micromanagement of the learning process, and hence explanations were provided for novice behaviour such as difficulties using arrays, inert knowledge and “code thrashing”. For teaching more complex problem solving, scaffolding of practice was investigated through a program framework that could be developed in stages by the students. However, personalising the level of scaffolding required was complicated and found to be difficult to achieve in practice. In both cases, these new teaching approaches evolved as part of a grounded theory study and a clear progression of teaching practice was demonstrated with appropriate evaluation at each stage in accordance with action researc

Reflection and Learning Robustness in a Natural Language Conceptual Physics Tutoring System

This thesis investigates whether reflection after tutoring with the Itspoke qualitative physics tutoring system can improve both near and far transfer learning and retention. This question is formalized in three major hypotheses. H1: that reading a post-tutoring reflective text will improve learning compared to reading a non-reflective text. H2: that a more cohesive reflective text will produce higher learning gains for most students. And H3: that students with high domain knowledge will learn more from a less cohesive text.In addition, this thesis addresses the question of which mechanisms affect learning from a reflective text. Secondary hypotheses H4 and H5 posit that textual cohesion and student motivation, respectively, each affect learning by influencing the amount of inference performed while reading.These hypotheses were tested by asking students to read a reflective/abstractive text after tutoring with the Itspoke tutor. This text compared dialog parts in which similar physics principles had been applied to different situations. Students were randomly assigned among two experimental conditions which got ``high' or ``low' cohesion versions of this text, or a control condition which read non-reflective physics material after tutoring.The secondary hypotheses were tested using two measures of cognitive load while reading: reading speeds and a self-report measure of reading difficulty.Near and far transfer learning was measured using sets of questions that were mostly isomorphic vs. non-isomorphic the tutored problems, and retention was measured by administering both an immediate and a delayed post-test. Motivation was measured using a questionnaire.Reading a reflective text improved learning, but only for students with a middle amount of motivation, confirming H1 for that group. These students also learned more from a more cohesive reflective text, supporting H2. Cohesion also affected high and low knowledge students significantly differently, supporting H3, except that high knowledge students learned best from high, not low cohesion text.Students with higher amounts of motivation did have higher cognitive load, confirming hypothesis H5 and suggesting that they engaged the text more actively. However, secondary hypothesis H4 failed to show a role for cognitive load in explaining the learning interaction between knowledge and cohesion demonstrated in H3

Genre-based literacy pedagogy: the nature and value of genre knowledge in teaching and learning writing on a university first year media studies course

A thesis submitted to the Faculty of Humanities, Uniiversity of Luton, in partial fulfilment of the requirements for the degree of Doctor of PhilosophyIn the teaching and learning of literacy, descriptions of text have a problematic status as a result of the growing understanding of literacy as both a cognitive process and a social practice. In the teaching of academic subjects at university, student text is not usually an object of study. The research in this thesis draws on a language based theory oflearning to place textual description at the centre of the teaching and learning of both literacy and academic subjects at university. Participant observation and practice-based research methods were used to implement a form of text-oriented literacy teaching and to explore its compatibility with processes and practices orientations to literacy. Over an eighteen month period, systemic functional grammar was used to investigate and describe the texts of a film studies classroom and the descriptions were used in genre based literacy pedagogy. The effects of the pedagogy are measured in terms of students' performance in an end of course assignment, students' accounts of their writing processes, and student and subject-tutor perception of the text description and the pedagogy. In the thesis, a linguistic description of a key curriculum genre -a Taxonomic Film Analysis -is presented. An account is given of the pedagogy by means of which this essay genre was represented in the film studies classroom as a realisation of choices from linguistic, conceptual and activity systems. Systemic functional grammar-based text description is seen to have provided a means whereby a literacy tutor could collaborate with a subject tutor to provide a subject-specific form of literacy teaching which was evaluated as relevant by students and tutors. The account and the evaluation help to clarify the role that description of text can play in relation to processes and practices ofliteracy use in the teaching and learning of literacy in a film studies classroom and have implications for the teaching and learning of literacy at university more generally

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

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