Intelligent tutoring systems: an overview

This is a non-expert overview of Intelligent Tutoring Systems (ITSs), a way in which Artificial Intelligence (AI) techniques are being applied to education. It introduces ITSs and the motivation for them. It looks at its history: its evolution from Computer-Assisted Instruction (CAI). After looking at the structure of a typical ITS, the paper further examines and discusses some other architectures. Several classic ITSs are reviewed, mainly due to their historical significance or because they best demonstrate some of the principles of intelligent tutoring. A reasonably representative list of ITSs is also provided in order to provide a better appreciation of this vibrant field as well as reveal the scope of existing tutors. The paper concludes, perhaps more appropriately, with some of the author's viewpoints on a couple of controversial issues in the intelligent tutoring domain.     

Information systems development as emergent socio-technical change: a practice approach

Many information systems development (ISD) initiatives fail to deliver the expected benefits. An important percentage of these are the result of social and organizational factors, not simply technical failures. This paper explores the dynamics of these social and organizational factors to better understand the causes of success and failure. Based on data from a detailed case analysis of an ISD project, the paper depicts the ISD process as an emergent and dynamic one, characterized by continuous local adaptations. The paper ends with a proposal of a feedback-rich framework, based on a practice view of socio-technical change that offers theoretical insights and practical heuristics to system developers and project managers.     

The evaluation of an intelligent tutoring system

Abstract

Numerous intelligent tutoring systems (ITSs) have been developed to date. However, one aspect of their development which is consistently ignored, judging from the literature, is the crucial activity of evaluation. It is also ironical that researchers generally agree that the benefits of this activity could be far-reaching. ITSs are often described to some degree of detail but an appraisal as to their (potential) usefulness is seldom given. The relative novelty of doing this was the main motivation for this paper, which starts by attempting to shed some light on why evaluation has become such a taboo activity, not only in intelligent tutoring, but in artificial intelligence (AI) research in general. It then overviews a tutor, the fractions intelligent tutoring system (FITS), and reports on how it was appraised. The approaches used are neither ideal nor generally accepted, but may well provide an adequate starting point in the belief that an attempt at an honest evaluation of any sort is better than no evaluation at all.     

Tracking recurring contexts using ensemble classifiers: an application to email filtering

Concept drift constitutes a challenging problem for the machine learning and data mining community that frequently appears in real world stream classification problems. It is usually defined as the unforeseeable concept change of the target variable in a prediction task. In this paper, we focus on the problem of recurring contexts, a special sub-type of concept drift, that has not yet met the proper attention from the research community. In the case of recurring contexts, concepts may re-appear in future and thus older classification models might be beneficial for future classifications. We propose a general framework for classifying data streams by exploiting stream clustering in order to dynamically build and update an ensemble of incremental classifiers. To achieve this, a transformation function that maps batches of examples into a new conceptual representation model is proposed. The clustering algorithm is then applied in order to group batches of examples into concepts and identify recurring contexts. The ensemble is produced by creating and maintaining an incremental classifier for every concept discovered in the data stream. An experimental study is performed using (a) two new real-world concept drifting datasets from the email domain, (b) an instantiation of the proposed framework and (c) five methods for dealing with drifting concepts. Results indicate the effectiveness of the proposed representation and the suitability of the concept-specific classifiers for problems with recurring contexts.     

基于Winpcap的邮件还原系统的实现

随着互联网的普及,SMTP/POP3协议传输方式下的邮件已成为最简便、最经济的通信方式,但许多有害的邮件信息也随之而来。针对这些问题,在VC开发环境下,研究并实现了基于Winpcap的邮件监控及还原系统。该系统设计了多线程模块,可以同时处理50个邮件及附件信息,并对网络数据包的捕获、过滤与重组、信头解码、附件处理、信体内容提取等模块进行了算法优化。功能测试和验证结果表明,该系统稳定、可扩展,达到实时性要求。     

Semantic email: theory and applications

This paper investigates how the vision of the Semantic Web can be carried over to the realm of email. We introduce a general notion of semantic email, in which an email message consists of a structured query or update coupled with corresponding explanatory text. Semantic email opens the door to a wide range of automated, email-mediated applications with formally guaranteed properties. In particular, this paper introduces a broad class of semantic email processes. For example, consider the process of sending an email to a program committee, asking who will attend the PC dinner, automatically collecting the responses, and tallying them up. We define both logical and decision-theoretic models where an email process is modeled as a set of updates to a data set on which we specify goals via certain constraints or utilities. We then describe a set of inference problems that arise while trying to satisfy these goals and analyze their computational tractability. In particular, we show that for the logical model it is possible to automatically infer which email responses are acceptable w.r.t. a set of constraints in polynomial time, and for the decision-theoretic model it is possible to compute the optimal message-handling policy in polynomial time. In addition, we show how to automatically generate explanations for a process's actions, and identify cases where such explanations can be generated in polynomial time. Finally, we discuss our publicly available implementation of semantic email and outline research challenges in this realm.¹     

Clinical reasoning gains in medical PBL: an UMLS based tutoring system

Problem based learning is becoming widely popular as an effective teaching method in medical education. Paying individual attention to a small group of students in medical problem-based learning (PBL) can place burden on the workload of medical faculty whose time is very costly. Intelligent tutoring systems offer a cost effective alternative in helping to train the students, but they are typically prone to brittleness and the knowledge acquisition bottleneck. Existing tutoring systems accept a small set of approved solutions for each problem scenario stored into the system. Plausible student solutions that lie outside the scope of the explicitly encoded ones receive little acknowledgment from the system. Tutoring hints are also confined to the knowledge space of the approved solutions, leading to brittleness in the tutoring approach. We report the clinical reasoning gains off a tutoring system for medical PBL that employs and represents the widely available medical knowledge source UMLS as the domain ontology. We exploit the structure of the concept hierarchy to expand the plausible solution space and generate hints based on the problem solving context. Evaluation of student learning outcomes led to highly significant learning gains (Mann-Whitney, p < 0.001).     

Managing email overload with an automatic nonparametric clustering system

Email overload is a recent problem that there is increasingly difficulty that people have to process the large number of emails received daily. Currently, this problem becomes more and more serious and it has already affected the normal usage of email as a knowledge management tool. It has been recognized that categorizing emails into meaningful groups can greatly save cognitive load to process emails, and thus this is an effective way to manage the email overload problem. However, most current approaches still require significant human input for categorizing emails. In this paper, we develop an automatic email clustering system, underpinned by a new nonparametric text clustering algorithm. This system does not require any predefined input parameters and can automatically generate meaningful email clusters. The evaluation shows our new algorithm outperforms existing text clustering algorithms with higher efficiency and quality in terms of computational time and clustering quality measured by different gauges. The experimental results also well match the labeled human clustering results.

Remote sensing of emergent and submerged wetlands: an overview

To plan for wetland protection and responsible coastal development, scientists and managers need to monitor changes in the coastal zone, as the sea level continues to rise and the coastal population keeps expanding. Advances in sensor design and data analysis techniques are now making remote-sensing systems practical and cost-effective for monitoring natural and human-induced coastal changes. Multispectral and hyperspectral imagers, light detection and ranging (lidar), and radar systems are available for mapping coastal marshes, submerged aquatic vegetation, coral reefs, beach profiles, algal blooms, and concentrations of suspended particles and dissolved substances in coastal waters. Since coastal ecosystems have high spatial complexity and temporal variability, they should be observed with high spatial, spectral, and temporal resolutions. New satellites, carrying sensors with fine spatial (0.4–4 m) or spectral (200 narrow bands) resolution, are now more accurately detecting changes in coastal wetland extent, ecosystem health, biological productivity, and habitat quality. Using airborne lidars, one can produce topographic and bathymetric maps, even in moderately turbid coastal waters. Imaging radars are sensitive to soil moisture and inundation and can detect hydrologic features beneath the vegetation canopy. Combining these techniques and using time-series of images enables scientists to study the health of coastal ecosystems and accurately determine long-term trends and short-term changes.     

RFID Applications: Interfacing with Readers

Improving efficiency is a major driver for increasing workflow automation and data integration, whether in software development or in application domains such as enterprise computing. Recently, RFID has been boosting workflow efficiency across production and supply networks. This physical identification technology relies on radio transmitters and receivers embedded in products of all types to itt >re and remotely retrieve data. It illustrates how the traditionally separate worlds of embedded and IT software are merging, and it demands skills in both worlds. Christian Floerkemeier and Flgar Fleisch describe the software issues in deploring RFID.     

Security services as coping mechanisms: an investigation into user intention to adopt an email authentication service

Email plays an important role in the digital economy but is threatened by increasingly sophisticated cybercrimes. A number of security services have been developed, including an email authentication service designed to cope with email threats. It remains unknown how users perceive and evaluate these security services and consequently form their adoption intention. Drawing on the Technology Acceptance Model and Technology Threat Avoidance Theory, this paper investigates the factors that affect user intention to adopt an email authentication service. Our results show that user intention to adopt an email security service is contingent upon users' perception of risk and evaluation of both internal and external coping strategies. This study contributes to research in security service adoption, service success and design, and information security behaviour.     

Intelligent tutoring systems: An overview

Abstract: In this paper we look at the evolutionary development of Computer Assisted Instruction from the early days of ‘linear programs’ up to the use of ‘expert systems’ in education and training. We present the basic principles of Intelligent Tutoring Systems (ITS) which are capable of rich interaction with the student, which know how to teach, and who and what they are teaching. We point out the need for knowledge representation formalisms which can support ITS and present one such formalism (production systems). In the framework presented we describe systems developed for the teaching of modern languages, electronic trouble shooting and computer programming. Finally we point out the shortcomings of ITS and identify areas where a consensus of opinion does not exist.     

How to replace an old email system with a new

All organizations that use email face changes in their email systems. While some of these are only a change of version that has little effect on the organization, many will replace old email systems with new ones, and this may have severe consequences. A case study is presented where the replacement of two old mainframe-based email systems with Lotus Notes failed. Based on this failure, seven important requirements are defined to reduce problems organizations face when replacing old email systems with new ones. These requirements are supported with results from other research.     

Interfacing digitiezed Disa anemometer output to an Apple II computer

For measuring the velocities in a fluctuating fluid flow, the new Disa 56C00 multichannel constant-temperature anemometer system can be used with the 56N00 signal analysis equipment to provide a digital output of mean, root mean square or correlation values. A simple interface arrangement and appropriate software control for reading data directly into an Apple II computer are described. With these the subsequent calculation of derived parameters, such as displacement and momentum thickness of boundary layers and turbulence intensity, can be quickly and easily completed.     

Developing an intelligent tutoring system for a business simulation game

Intelligent Tutoring Systems and gaming-simulation are both substantive research and application areas which cross a multitude of disciplines and subject areas. However, although the two areas have the potential for mutual enhancement, very little has been reported on to this effect. This paper proposes an architecture for an Intelligent Tutoring System for an existing business simulation game. The short-term aim of this paper is to show how the pedagogical effectiveness of an existing gaming-simulation environment, as a teaching and learning tool, can be enhanced through the Intelligent Tutoring Systems approach to development. The long-term aim is to highlight a possible direction towards any mutual enhancement.     

An object-oriented software life cycle of an intelligent tutoring system

Abstract  This paper describes the application of an object-oriented model of life cycle in the development of an intelligent tutoring system for secondary students in the domain of algebraic powers. The system is called EasyMath and has been developed using the Rational Unified Process, which is an object-oriented process proposed for use with the Unified Modelling Language. The Rational Unified Process supports multiple recursions of the phases of the software life cycle. This has been enriched to include empirical studies and formative evaluations appropriate for knowledge-based educational software.     

An adaptation algorithm for an intelligent natural language tutoring system

The focus of computerised learning has shifted from content delivery towards personalised online learning with Intelligent Tutoring Systems (ITS). Oscar Conversational ITS (CITS) is a sophisticated ITS that uses a natural language interface to enable learners to construct their own knowledge through discussion. Oscar CITS aims to mimic a human tutor by dynamically detecting and adapting to an individual's learning styles whilst directing the conversational tutorial. Oscar CITS is currently live and being successfully used to support learning by university students. The major contribution of this paper is the development of the novel Oscar CITS adaptation algorithm and its application to the Felder–Silverman learning styles model. The generic Oscar CITS adaptation algorithm uniquely combines the strength of an individual's learning style preference with the available adaptive tutoring material for each tutorial question to decide the best fitting adaptation. A case study is described, where Oscar CITS is implemented to deliver an adaptive SQL tutorial. Two experiments are reported which empirically test the Oscar CITS adaptation algorithm with students in a real teaching/learning environment. The results show that learners experiencing a conversational tutorial personalised to their learning styles performed significantly better during the tutorial than those with an unmatched tutorial.     

The role of probability-based inference in an intelligent tutoring system

Probability-based inference in complex networks of interdependent variables is an active topic in statistical research, spurred by such diverse applications as forecasting, pedigree analysis, troubleshooting, and medical diagnosis. This paper concerns the role of Bayesian inference networks for updating student models in intelligent tutoring systems (ITSs). Basic concepts of the approach are briefly reviewed, but the emphasis is on the considerations that arise when one attempts to operationalize the abstract framework of probability-based reasoning in a practical ITS context. The discussion revolves around HYDRIVE, an ITS for learning to troubleshoot an aircraft hydraulics system. HYDRIVE supports generalized claims about aspects of student proficiency through probabilitybased combination of rule-based evaluations of specific actions. The paper highlights the interplay among inferential issues, the psychology of learning in the domain, and the instructional approach upon which the ITS is based.     

Designing for pen and speech input in an object-action framework: the case of email

This study presents a user interface that was intentionally designed to support multimodal interaction by compensating for the weaknesses of speech compared with pen input and vice versa. The test application was email using a web pad with pen and speech input. In the case of pen input, information was represented as visual objects, which were easily accessible. Graphical metaphors were used to enable faster and easier manipulation of data. Speech input was facilitated by displaying the system speech vocabulary to the user. All commands and accessible fields with text labels could be spoken in by name. Commands and objects that the user could access via speech input were shown on a dynamic basis in a window. Multimodal interaction was further enhanced by creating a flexible object-action order such that the user could utter or select a command with a pen followed by the object which was to be enacted upon, or the other way round (e.g., New Message or Message New). The flexible action-object interaction design combined with voice and pen input led to eight possible action-object-modality combinations. The complexity of the multimodal interface was further reduced by making generic commands such as New applicable across corresponding objects. Use of generic commands led to a simplification of menu structures by reducing the number of instances in which actions appeared. In this manner, more content information could be made visible and consistently accessible via pen and speech input. Results of a controlled experiment indicated that the shortest task completion times for the eight possible input conditions were when speech-only was used to refer to an object followed by the action to be performed. Speech-only input with action-object order was also relatively fast. In the case of pen input-only, the shortest task completion times were found when an object was selected first followed by the action to be performed. In multimodal trials in which both pen and speech were used, no significant effect was found for object-action order, suggesting benefits of providing users with a flexible action-object interaction style in multimodal or speech-only systems.