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

System upgrade: realising the vision for UK education

A report summarising the findings of the TEL programme in the wider context of technology-enhanced learning and offering recommendations for future strategy in the area was launched on 13th June at the House of Lords to a group of policymakers, technologists and practitioners chaired by Lord Knight. The report – a major outcome of the programme – is written by TEL director Professor Richard Noss and a team of experts in various fields of technology-enhanced learning. The report features the programme’s 12 recommendations for using technology-enhanced learning to upgrade UK education

Intelligent Tutoring System Authoring Tools for Non-Programmers

An intelligent tutoring system (ITS) is a software application that tries to replicate the performance of a human tutor by supporting the theory of learning by doing . ITSs have been shown to improve the performance of a student in wide range of domains. Despite their benefits, ITSs have not seen widespread use due to the complexity involved in their development. Developing an ITS from scratch requires expertise in several fields including computer science, cognitive psychology and artificial intelligence. In order to decrease the skill threshold required to build ITSs, several authoring tools have been developed. In this thesis, I document several contributions to the field of intelligent tutoring in the form of extensions to an existing ITS authoring tool, research studies on authoring tool paradigms and the design of authoring tools for non-programmers in two complex domains - natural language processing and 3D game environments. The Extensible Problem Specific Tutor (xPST) is an authoring tool that helps rapidly develop model-tracing like tutors on existing interfaces such as webpages. xPST\u27s language was made more expressive with the introduction of new checktypes required for answer checking in problems belonging to domains such as geometry and statistics. A web-based authoring (WAT) tool was developed for the purpose of tutor management and deployment and to promote non-programmer authoring of ITSs. The WAT was used in a comparison study between two authoring tool paradigms - GUI based and text based, in two different problem domains - statistics and geometry. User-programming of natural language processing (NLP) in ITSs is not common with authoring toolkits. Existing NLP techniques do not offer sufficient power to non-programmers and the NLP is left to expert developers or machine learning algorithms. We attempted to address this challenge by developing a domain-independent authoring tool, ConceptGrid that is intended to help non-programmers develop ITSs that perform natural language processing. ConceptGrid has been integrated into xPST. When templates created using ConceptGrid were tested, they approached the accuracy of human instructors in scoring student responses. 3D game environments belong to another domain for which authoring tools are uncommon. Authoring game-based tutors is challenging due to the inherent domain complexity and dynamic nature of the environment. We attempt to address this challenge through the design of authoring tool that is intended to help non-programmers develop game-based ITSs

Mapping Big Data into Knowledge Space with Cognitive Cyber-Infrastructure

Big data research has attracted great attention in science, technology, industry and society. It is developing with the evolving scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies. However, its nature and fundamental challenge have not been recognized, and its own methodology has not been formed. This paper explores and answers the following questions: What is big data? What are the basic methods for representing, managing and analyzing big data? What is the relationship between big data and knowledge? Can we find a mapping from big data into knowledge space? What kind of infrastructure is required to support not only big data management and analysis but also knowledge discovery, sharing and management? What is the relationship between big data and science paradigm? What is the nature and fundamental challenge of big data computing? A multi-dimensional perspective is presented toward a methodology of big data computing.Comment: 59 page

Exploring Problem Solving Paths in a Java Programming Course

Assessment of students’ programming submissions has been the focus of interest in many studies. Although the final submissions capture the whole program, they often tell very little about how it was developed. In this paper, we are able to look at intermediate programming steps using a unique dataset that captures a series of snapshots showing how students developed their program over time. We assessed each of these intermediate steps and performed a fine-grained concept-based analysis on each step to identify the most common programming paths. Analysis of results showed that most of the students tend to incrementally build the program and improve its correctness. This finding provides us with evidence that intermediate programming steps are important, and need to be taken into account for not only improving user modelling in educational programming systems, but also for providing better feedback to students

Development of an autonomous distributed multiagent monitoring system for the automatic classification of end users

The purpose of this study is to investigate the feasibility of constructing a software Multi-Agent based monitoring and classification system and utilizing it to provide an automated and accurate classification for end users developing applications in the spreadsheet domain. Resulting in, is the creation of the Multi-Agent Classification System (MACS). The Microsoft‘s .NET Windows Service based agents were utilized to develop the Monitoring Agents of MACS. These agents function autonomously to provide continuous and periodic monitoring of spreadsheet workbooks by content. .NET Windows Communication Foundation (WCF) Services technology was used together with the Service Oriented Architecture (SOA) approach for the distribution of the agents over the World Wide Web in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus agent oriented design methodology and its accompanying Prometheus Design Tool (PDT) was employed for specifying and designing the agents of MACS, and Visual Studio.NET 2008 for creating the agency using visual C# programming language. MACS was evaluated against classification criteria from the literature with the support of using real-time data collected from a target group of excel spreadsheet developers over a network. The Monitoring Agents were configured to execute automatically, without any user intervention as windows service processes in the .NET web server application of the system. These distributed agents listen to and read the contents of excel spreadsheets development activities in terms of file and author properties, function and formulas used, and Visual Basic for Application (VBA) macro code constructs. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers. Oracle data mining classification algorithms: Naive Bayes, Adaptive Naive Bayes, Decision Trees, and Support Vector Machine were utilized to analyse the results from the data gathering process in order to automate the classification of excel spreadsheet developers. The accuracy of the predictions achieved by the models was compared. The results of the comparison showed that Naive Bayes classifier achieved the best results with accuracy of 0.978. Therefore, the MACS can be utilized to provide a Multi-Agent based automated classification solution to spreadsheet developers with a high degree of accuracy

SAT based Enforcement of Domotic Effects in Smart Environments

The emergence of economically viable and efficient sensor technology provided impetus to the development of smart devices (or appliances). Modern smart environments are equipped with a multitude of smart devices and sensors, aimed at delivering intelligent services to the users of smart environments. The presence of these diverse smart devices has raised a major problem of managing environments. A rising solution to the problem is the modeling of user goals and intentions, and then interacting with the environments using user defined goals. `Domotic Effects' is a user goal modeling framework, which provides Ambient Intelligence (AmI) designers and integrators with an abstract layer that enables the definition of generic goals in a smart environment, in a declarative way, which can be used to design and develop intelligent applications. The high-level nature of domotic effects also allows the residents to program their personal space as they see fit: they can define different achievement criteria for a particular generic goal, e.g., by defining a combination of devices having some particular states, by using domain-specific custom operators. This paper describes an approach for the automatic enforcement of domotic effects in case of the Boolean application domain, suitable for intelligent monitoring and control in domotic environments. Effect enforcement is the ability to determine device configurations that can achieve a set of generic goals (domotic effects). The paper also presents an architecture to implement the enforcement of Boolean domotic effects, and results obtained from carried out experiments prove the feasibility of the proposed approach and highlight the responsiveness of the implemented effect enforcement architectur

Authoring Effective Embedded Tutors: An Overview of the Extensible Problem Specific Tutor (xPST) System

The Extensible Problem Specific Tutor (xPST) allows authors who are not cognitive scientists and not programmers to quickly create an intelligent tutoring system that provides instruction akin to a model-tracing tutor. Furthermore, this instruction is overlaid on existing software, so that the learner’s interface does not have to be made from scratch. The xPST architecture allows for extending its capabilities by the addition of plug-ins that communicate with additional third-party software. After reviewing this general architecture, we describe three major implementations that we have created using the xPST system, each using different third-party software as the learner’s interface. We have conducted three evaluations of authors using xPST to create tutoring content, and these are considered in turn. These evaluations show that xPST authors can quickly learn the system, and can efficiently produce successful embedded instruction

Authoring Example-based Tutors for Procedural Tasks

Researchers who have worked on authoring systems for intelligent tutoring systems (ITSs) have examined how examples may form the basis for authoring. In this chapter, we describe several such systems, consider their commonalities and differences, and reflect on the merit of such an approach. It is not surprising perhaps that several tutor developers have explored how examples can be used in the authoring process. In a broader context, educators and researchers have long known the power of examples in learning new material. Students can gather much information by poring over a worked example, applying what they learn to novel problems. Often these worked examples prove more powerful than direct instruction in the domain. For example, Reed and Bolstad (1991) found that students learning solely by worked examples exhibited much greater learning than those learning instruction based on procedures. By extension then, since tutor authoring can be considered to be teaching a tabula rasa tutor, tutor authoring by use of examples may be as powerful as directly programming the instruction, while being easier to do