James Harland

Evaluating the Quality of Interaction in Asynchronous Discussion Forums in Fully Online Courses

Fully online courses are becoming progressively more popular because of their “anytime anywhere” learning flexibility. One of the ways students interact with each other and with the instructors within fully online learning environments is via asynchronous discussion forums. However, student engagement in online discussion forums does not always take place automatically and there is a lack of clarity about the ideal role of the instructors in them. In this article, we report on our research on the quality of discussion in fully online courses through analysis of discussion forum activities. We have conducted our research on two large fully online subjects for computing students over two consecutive semesters and used a grounded theoretic approach for data analysis. Our results reveal what students and instructors consider as quality interaction in fully online courses. We also propose two frameworks based on our findings that can be used to ensure effective online interaction.

Simplifying the Development of Intelligent Agents

Intelligent agents is a powerful Artificial Intelligence technology which shows considerable promise as a new paradigm for mainstream software development. However, despite their promise, intelligent agents are still scarce in the market place. A key reason for this is that developing intelligent agent software requires significant training and skill: a typical developer or undergraduate struggles to develop good agent systems using the Belief Desire Intention (BDI) model (or similar models). This paper identifies the concept set which we have found to be important in developing intelligent agent systems and the relationships between these concepts. This concept set was developed with the intention of being clearer, simpler, and easier to use than current approaches. We also describe briefly a (very simplified) example from one of the projects we have worked on (RoboRescue), illustrating the way in which these concepts are important in designing and developing intelligent software agents.

Enhancing commitment machines

Agent interaction protocols are usually specified in terms of permissible sequences of messages. This representation is, unfortunately, brittle and does not allow for flexibility and robustness. The commitment machines framework of Yolum and Singh aims to provide more flexibility and robustness by defining interactions in terms of the commitments of agents. In this paper we identify a number of areas where the commitment machines framework needs improvement and propose an improved version. In particular we improve the way in which commitments are discharged and the way in which pre-conditions are specified.

Representation and reasoning for goals in BDI agents

A number of agent-oriented programming systems are based on a framework of beliefs, desires and intentions (BDI) and more explicitly on the BDI logic of Rao and Georgeff. In this logic, goals are a consistent set of desires, and this property is fundamental to the semantics of the logic. However, implementations based on this framework typically have no explicit representation of either desires or goals, and consequently no mechanisms for checking consistency. In this paper we address this gap between theory and practice by giving an explicit representation for a simple class of desires. The simplicity of this class makes it both straightforward and efficient to check for consistency. We provide a general framework for conflict resolution based on a preference ordering of sets of goals, and we illustrate how different rules for specifying consistent goal sets (corresponding to different preference orderings) relate to existing commitment strategies. We also report on some implementation experiments which confirm that the cost of consistency maintenance is not significant.

On proactivity and maintenance goals

Goals are an important concept in intelligent agent systems, and can take a variety of forms. One such form is maintenance goals, which, unlike achievement goals, define states that must remain true, rather than a state that is to be achieved. Maintenance goals are generally restricted to acting as trigger conditions for goals or plans, and often take no part in any deliberation process. These goals are reactive and are only acted upon when the maintenance conditions are no longer true. In this paper, we study maintenance goals that are proactive, in that the agent system needs to not only react when the maintenance conditions fail, but also anticipate the failures of these conditions, and act in order to avoid them failing. This can be done by performing actions that prevent the condition from failing, or suspending goals that will cause the maintenance conditions to fail. We provide a representation for maintenance goals that captures both their reactive and proactive aspects, algorithms that identify in advance where maintenance conditions may not hold, and mechanisms for enabling preventative actions in such situations. We also provide some experimental results on an implementation of these ideas.

Aborting tasks in BDI agents

Intelligent agents that are intended to work in dynamic environments must be able to gracefully handle unsuccessful tasks and plans. In addition, such agents should be able to make rational decisions about an appropriate course of action, which may include aborting a task or plan, either as a result of the agents own deliberations, or potentially at the request of another agent. In this paper we investigate the incorporation of aborts into a BDI-style architecture. We discuss some conditions under which aborting a task or plan is appropriate, and how to determine the consequences of such a decision. We augment each plan with an optional abort-method, analogous to the failure method found in some agent programming languages. We provide an operational semantics for the execution cycle in the presence of aborts in the abstract agent language CAN, which enables us to specify a BDI-based execution model without limiting our attention to a particular agent system (such as JACK, Jadex, Jason, or SPARK). A key technical challenge we address is the presence of parallel execution threads and of sub-tasks, which require the agent to ensure that the abort methods for each plan are carried out in an appropriate sequence.

Resource-distribution via Boolean constraints

We consider the problem of searching for proofs in sequential presentations of logics with multiplicative (or intensional) connectives. Specifically, we start with the multiplicative fragment of linear logic and extend, on the one hand, to linear logic with its additives and, on the other, to the additives of the logic of bunched implications (BI). We give an algebraic method for calculating the distribution of the side-formulæ in multiplicative rules which allows the occurrence or non-occurrence of a formula on a branch of a proof to be determined once sufficient information is available. Each formula in the conclusion of such a rule is assigned a Boolean expression. As a search proceeds, a set of Boolean constraint equations is generated. We show that a solution to such a set of equations determines a proof corresponding to the given search. We explain a range of strategies, from the lazy to the eager, for solving sets of constraint equations. We indicate how to apply our methods systematically to large family of relevant systems.

Exploring programming assessment instruments: a classification scheme for examination questions

This paper describes the development of a classification scheme that can be used to investigate the characteristics of introductory programming examinations. We describe the process of developing the scheme, explain its categories, and present a taste of the results of a pilot analysis of a set of CS1 exam papers. This study is part of a project that aims to investigate the nature and composition of formal examination instruments used in the summative assessment of introductory programming students, and the pedagogical intentions of the educators who construct these instruments.

Matching Strictly Dependent Global Constraints for Composite Web Services

Web service discovery requires matching techniques for comparing and selecting web service descriptions based on user constraints. Semantic-based approaches achieve higher recall than other approaches (such as syntax-based approaches), because they employ ontological reasoning mechanisms to match syntactically heterogeneous descriptions. However, existing semantic-based approaches are not scalable as they perform an exhaustive search to locate composite services that conform to global constraints. This paper proposes a semantic-based matching technique that locates composite services. It relates attributes of services to a common attribute to ensure that they have the same scope. This enables the assigned values to be compared and evaluated against a given global constraint. Conforming composite services are located in polynomial time with a three-dimensional data structure that indexes services based on their types, attributes and the assigned values. Simulation results indicate that the proposed approach achieves higher recall than syntax-based approaches and is more scalable than existing semantic-based approaches.

Agent negotiation as proof search in linear logic

Negotiation is a key aspect of multi-agent systems, and one which clearly requires appropriate reasoning processes. Fisher [2] has introduced the notion of negotiation as theorem proving, in which the agents can reach a satisfactory arrangement iff there is proof in a given system. Fisher’s system is based on a distributed theorem proving environment employing resolution techniques in classical logic. In this paper we show how a basis in linear logic enables a richer (and arguably more natural) basis for reasoning about negotiations. In particular (i) the representation of conditionals is direct and natural in linear logic; (ii) linear logic allows for consumables to be modelled; and (iii) linear logic allows varying types of choices to be modelled in a clearer way than using classical logic. This last is of particular importance – there is an important distinction between an agent that is willing to provide clothing or food where another agent makes the choice, and an agent that is willing to provide either clothing or food but where that agent chooses between them. Hence the contribution of this paper is to provide a more natural basis for the reasoning required. In this sense our focus is on the outcome of the negotiation, rather than the (possibly argumentative) process. In particular, we assume that each party specifies what it desires, and the negotiation process presented finds solutions that satisfy all parties.