This study examines the relationships between information and communication technologies (ICT) usage, the benefits a company derives from membership in a rural business cluster, and the success of rural companies. Analysis of 333 rural businesses located in northern lower Michigan showed a strong relationship between (a) ICT adoption and benefits derived from the membership in business clusters, (b) ICT adoption and self-reported business success, and (c) benefits derived from business clusters and business success. Although analysis indicates that these relationships may be industry specific, results suggest that ICT adoption by rural enterprises may have advantages for the region’s social capital and
business success and may help reduce the digital divide experienced
in rural communities.
Efforts to promote sustainable broadband Internet adoption urge new attention to the classic diffusion of innovations paradigm. For this study, innovation attributes were reconceptualized following Social Cognitive Theory (SCT). In a sample of inner-city residents, the model accounted for 36% of the variance in intentions to adopt broadband technology and services, primarily from the SCT variables of expected outcomes and self-efficacy. Prior habitual use of the Internet was also a predictor. Price sensitivity was unrelated to adoption. Among demographic variables, only age had a significant (negative) relationship to broadband adoption after accounting for the SCT variables. Recommendations for the design and monitoring of sustainable broadband adoption interventions are made based on these findings.
The television landscape is in a state of flux. In this new environment, profit-driven media companies have to balance tradeoffs between traditional and new channels of video distribution to optimize returns on their investments in content generation. This chapter describes the challenges traditional television service providers face in adapting their strategies to an environment in which the internet is playing an increasingly prominent role as a new distribution channel. In the short to intermediate run there is the challenge of finding ways to monetize an internet audience without cannibalizing profits earned through traditional distribution channels. The longer-term challenge is adapting to a distribution technology that embeds a fundamentally different economic logic for video market organization. In this chapter, we describe and analyze current trends in the internet television market and traditional television industry players’ efforts to respond to the opportunities and threats posed by internet distribution.
This paper presents the rationale behind the utilization of a Moodle Learning Management System for the facilitation of a blended learning approach in our Informatics department. We present and analyze the steps followed in order to replace the prior decentralized organizational structure of the courses, which consisted of a multitude of different and incompatible systems. Our main goal was to implement a single system, which would be easy to operate, maintain, and update, and which would cater for the variety of instructor and stu-dent needs. Furthermore, we present in detail evaluation data of the new system. The analysis of the results serves to confirm the success of this department-wide migration.
Purpose – The purpose of this paper is to explore the impact of question prompts on student learning in relation to their learning styles. The context of the study is technology-enhanced learning in an ill-structured domain.
Design/methodology/approach – The study conditions were the same for all the students in the four learning style groups. Student learning style was the independent variable, while students’ attitudes and task performance were the dependent variables of the study. Pre-test treatment post-test method was used. Students studied in a web-based learning environment during treatment.
Findings – The integration of question prompts as student supporting tool in technology-enhanced learning environments might not improve learning for all students alike independent of their learning styles.
Research limitations/implications – Small uneven groups because the researcher has no control over the student distribution across the different learning style profiles.
Practical implications – The suggestion for designers is to consider combining prompting with other scaffolding methods, in order to effectively support all students independent of their learning styles.
Originality/value – The paper combines learning in ill-structured domains through cases and a scaffolding method based on question prompts focusing on contextual elements. The results of the study inform the designers of TELEs that although prompting can be generally helpful, parameters such as the students’ learning style are able to limit the cognitive benefit emerging from the prompting intervention.
This study investigates the effectiveness of two variants of a prompting strategy that guides students to focus on important issues when learning in an ill-structured
domain. Students in three groups studied individually Software Project Management (SPM) cases for a week, using a web-based learning environment designed especially for
this purpose. The first group (control) studied the cases without any prompting. The second group (‘‘writing mode’’) studied the same cases, while prompted to provide written
answers to a set of knowledge integration prompts meant to engage students in deeper processing of the material. The third group (‘‘thinking mode’’) studied the cases, while
prompted only to think of possible answers to the same question prompts. Results indicated that students in the writing condition group outperformed the others in both domain knowledge acquisition and knowledge transfer post-test items. Several students in the thinking condition group skipped the question prompts, while those that reported having reflected on the material were unable to achieve high performance comparable to the writing condition group. Overall, the study provides evidence that the implementation of prompting techniques in technology-enhanced learning environments may lead to improved outcomes, when combined with the requirement that students provide their answers in writing.
This study was designed to investigate the impact of question prompts that guide students to focus on context-related issues when learning through cases in an illstructured
domain. Three groups of undergraduate students studied cases during a lab-session time period using a web-based environment. The first group studied without any
question prompts. The second group studied the same material while prompted to provide written answers to embedded questions in the cases. The third group studied while having only to think of possible answers for the question prompts. In this study, we explored how the questioning intervention affected students’ conceptual knowledge of the domain and their problem-solving ability. Post-tests did not reveal significant statistical differences in the groups’ performance, indicating that under specific study conditions the prompting impact is not traceable in the learning outcomes. This result, however, is discussed in the light of a previous study, which showed that this context-oriented prompting method had a beneficial effect on student learning in a prolonged study-time setting, where students were able to self-regulate their study activity.
This Report shows the application of model checking techniques over formal specifications expressed in RSL using the FRD2 refinement checker, for which we have developed a first version of a translator from RSL to CSPM. We give an overview of the semantic and syntactic differences between these two languages, then we define a translation subset and finally we show the strategy used to find the respective equivalences in order to make the translation possible; we also briefly describe the development of the translator and show the use of this translator with some typical concurrent examples.
This work focuses on the efficiency of question prompts for supporting students, when learning through cases in an ill-structured domain, such as Software Project Management. Three groups of students studied cases in a lab-session time period using a web-based environment, where question prompts directed students to think on important issues of the case material. The first group studied the cases without the question prompts, the second group studied, while prompted to provide written answers to questions embedded in the cases, and the third group studied and was asked only to think of possible answers for the question prompts. Post-tests did not reveal any significant differences between the three groups. This result is discussed in the light of a previous study, which showed that this kind of prompting may have beneficial impact on student learning in a prolonged study-time setting, where students are able to self-regulate their study activity.
This paper presents the rationale behind the utilization of the Moodle Learning Management System for blended learning in our Informatics Department and examines the steps followed, to replace the prior decentralized course organizational structure which consisted of a multitude of different systems. Our main goal was to implement a single, easy-to-operate, easy-to-maintain system, able to support students’ and instructors’ needs in all the courses. Further-more, we present data which describe the pilot study of the Moodle implementation for the first semester and make evident the success of the department-wide migration.
Effectively selling products online is a challenging task. Today's product domains often contain a dizzying variety of brands and models with highly complex sets of characteristics. This paper addresses the problem of supporting product search and selection in domains containing large numbers of alternatives with complex sets of features. A number of online shopping websites provide product choice assistance by making direct use of Multi-Attribute Utility Theory (MAUT). While the MAUT approach is appealing due to its solid theoretical foundations, there are several reasons that it does not fit well with people's decision making behavior.This paper presents an approach designed to better fit with people's natural decision making process. The system is called VMAP for Visualizing Multi-Attribute Preferences. VMAP provides on one screen both a multi-attribute preference tool (MAP-tool) and a product visualization tool (V-tool). The product visualization tool displays the set of available products, with each product displayed as a point in a 3D attribute space. By viewing the product space, users can gain an overview of the range of available products, as well as an understanding of the relationships between their attributes. The MAP-tool integrates expression of preferences and filter conditions, which are then immediately reflected in the V-tool display. In this way, the user can immediately see the consequences of his expressed preferences on the product space.The VMAP system is evaluated on a number of factors by comparing users' subjective ratings of the system to those of a more traditional MAUT product selection tool. The results show that while VMAP is somewhat more difficult to use than a traditional MAUT product selection tool, it provides better flexibility, provides the ability to more effectively explore the product domain, and produces more confidence in the selected product.
This paper presents a novel approach to deriving probabilistic models that predict enrollment given applicant background and the amount of financial aid offered. Our Bayesian network models can be used to optimize various enrollment objectives. We present a novel efficient optimization algorithm that uses the models to maximize expected tuition revenue under capacity constraints including student-faculty ratio and accommodation. We demonstrate and evaluate our approach using four years of graduate admissions data from the Asian Institute of Technology, consisting of 7,788 applicants from 84 different countries. This data set is particularly challenging since reliable family income data is not available for students from most of these countries. Evaluating the Bayesian network model with 10-fold cross validation yields an ROC Az value of 0.8451, with a predictive accuracy of 82.70% at a threshold of 0.5. Comparing the results of the tuition revenue optimization model to the institute’s current financial aid allocation practice shows that if single-term tuition revenue is the sole optimization criterion, the institute can achieve its current enrollment numbers while realizing significant savings in its financial aid budget. The prediction and optimization software is currently being incorporated into the institute’s online admissions processing system.
The aim of this work is to develop a template for component-based programs which can be used in different programming languages. First, we give a model of component based systems based on the unifying theory of programming. We define the concepts interface, contract and component, and component combination. The definition can be used as the basis for the component template development. We define a contract to include method specification, and define a component as an implementation of a contract. This implementation may require services from other components with some assumptions about the schedule for resolving the conflict of shared method and resource uses with the presence of concurrency. The assumption is expressed as interaction protocols. In our model, components are correct by its design. We then give a guideline for extending the model for real-time component systems.
This paper proposes a notion, the `ambit' of an action, that allows the degree of distribution of an action in a multi-agent system to be quantied without regard to its functionality. It demonstrates the use of that notion in the design, analysis and implementation of dynamicallyrecon gurable multi-agent systems. It distinguishes between the extensional (or system) view and intensional (or agent-based) view of such a system and shows how, using the notion of ambit, the step-wise derivation paradigm of Formal Methods can be used to derive the latter from the former. In closing it addresses the manner in which these ideas inform studies in the ethics of systems of articial agents.
Case-based learning is expected to enhance students’ awareness of the various contextual factors, which affect problem solving in ill structured domains. An interesting question is always how to engage students in efficient processing of the case-based learning material. In this work, we present the design and preliminary evaluation results of the eCASE environment, a generic web-based environment for supporting case-based instruction. eCASE allows instructors to develop appropriate study paths for students to criss-cross the case-based information landscape. Furthermore, it supports students’ study by providing scripts, which scaffold them when processing the learning material. A script in eCASE models the cognitive processes related to context awareness and guides students to focus on important events, recall relative cases and reach useful conclusions. First evaluation results indicate that students acknowledge the learning efficiency of scripted material. However, design improvements are also necessary to make scripts more appealing and less monotonous for students.
Supporting students' awareness of the complex way that contextual issues affect knowledge application in authentic situations is a critical instructional mission and can lead to improved problem solving in the workplace. In this work we present the design of e-CASE (Context Awareness Supporting Environment), which is a case based learning environment for supporting instruction in the domain of software development. In designing e-CASE we employ a model for context which further guides the use of script and narrative control techniques as external representations for enhancing students' context awareness. Our system applies an appropriate metadata scheme for connecting various pieces of information and creating crossing paths for the learner, in the web of authentic application cases. It also provides functionality for updating and extending its content allowing people from the workplace to become content providers. Thus, we argue, e-CASE can help bridging the contextual distance, supporting the development of an extended learning community by establishing flexible and instructionally efficient links between the traditional educational settings and the workplace.
This report aims at developing a technique for verifying if a timed automaton satisfies a linear duration constraint on the automaton states. The constraints are represented in the form of linear duration invariants - a simple class of Chop-free Duration Calculus (DC) formulas. We prove that linear duration invariants of a timed automaton are discretisable, and reduce checking if a timed automaton satisfies a linear duration invariant to checking if the integer timed region graph of the original automaton satisfies the same linear duration invariant. The latter can be done with exhausted search on graphs. In comparison to the techniques in the literatures, our one is more powerful; it works for the standard semantics of DC and general form of timed automata while the others cannot be applied.
In this paper, we consider the problem of checking hybrid systems modelled by hybrid automata for a class of duration properties called linear duration invariants, which are constructed from linear inequalities of integrated durations of system states. Based on linear programming, an algorithm is developed for checking a class of hybrid automata for linear duration invariants.
In this paper, we consider the problem of checking hybrid systems modelled by hybrid automata for a class of duration properties called linear duration invariants, which are constructed from linear inequalities of integrated durations of system states. Based on linear programming, an algorithm is developed for checking a class of hybrid automata for linear duration invariants