Information problem‐solving skills in small virtual groups and learning outcomes

This study investigated the frequency of use of information problem‐solving (IPS) skills and its relationship with learning outcomes. During the course of the study, 40 teachers carried out a collaborative IPS task in small virtual groups in a 4‐week online training course. The status of IPS skills was collected through self‐reports handed in over the course of the 4 weeks. Learning was evaluated by means of open‐ended questionnaires before and after the group task. Three types of knowledge learning were evaluated: declarative, procedural and situational. Teachers exhibited a recurrent use of all skills during the whole collaborative task, although periodic use differed from week to week. Results showed a relationship between some IPS skills and declarative and procedural knowledge. The skills that were statistically significant were share information, read peer's information and analyse information. Implications for learning support and instruction are discussed.     

S4W: a problem‐solving environment for wireless system design

This work describes the Site‐Specific System Simulator for Wireless System Design (S⁴W), a problem‐solving environment (PSE) that integrates visualization and computational tools with a high‐level graphical user interface. S⁴W improves the ability of wireless system engineers to design an indoor wireless system by encouraging them to think in terms of designing the system for optimal performance. Issues of computation management, data management, and location of resources are hidden from the user. The complex nature of data sets in the domain of wireless simulations calls for a customized set of visualization tools. Therefore, a number of ad hoc visualizations were developed for S⁴W. A study comparing the integrated system with an earlier, unintegrated version is presented. This helps to demonstrate the productivity gains that a PSE provides. Copyright © 2007 John Wiley & Sons, Ltd.     

A Grid‐enabled problem‐solving environment for advanced reservoir uncertainty analysis

Uncertainty analysis is critical for conducting reservoir performance prediction. However, it is challenging because it relies on (1) massive modeling‐related, geographically distributed, terabyte, or even petabyte scale data sets (geoscience and engineering data), (2) needs to rapidly perform hundreds or thousands of flow simulations, being identical runs with different models calculating the impacts of various uncertainty factors, (3) an integrated, secure, and easy‐to‐use problem‐solving toolkit to assist uncertainty analysis. We leverage Grid computing technologies to address these challenges. We design and implement an integrated problem‐solving environment ResGrid to effectively improve reservoir uncertainty analysis. The ResGrid consists of data management, execution management, and a Grid portal. Data Grid tools, such as metadata, replica, and transfer services, are used to meet massive size and geographically distributed characteristics of data sets. Workflow, task farming, and resource allocation are used to support large‐scale computation. A Grid portal integrates the data management and the computation solution into a unified easy‐to‐use interface, enabling reservoir engineers to specify uncertainty factors of interest and perform large‐scale reservoir studies through a web browser. The ResGrid has been used in petroleum engineering. Copyright © 2008 John Wiley & Sons, Ltd.     

An analysis of collaborative problem‐solving activities mediated by individual‐based and collaborative computer simulations

Researchers have indicated that the collaborative problem‐solving space afforded by the collaborative systems significantly impact the problem‐solving process. However, recent investigations into collaborative simulations, which allow a group of students to jointly manipulate a problem in a shared problem space, have yielded divergent results regarding their effects on collaborative learning. Hence, this study analysed how students solved a physics problem using individual‐based and collaborative simulations to understand their effects on science learning. Multiple data sources including group discourse, problem‐solving activities, learning test scores, and questionnaire feedback were analysed. Lag sequential analysis on the data found that students using the two simulations collaborated with peers to solve the problem in significantly different patterns. The students using the collaborative simulations demonstrated active engagement in the collaborative activity; however, they did not transform discussions into workable problem‐solving activities. The students using the individual‐based simulation showed a lower level of collaboration engagement, starting with individual exploration of the problem with the simulation, followed by group reflection. The two groups also showed significant differences in their learning test scores. The findings and pedagogical suggestions are discussed in the hope of addressing critical activity design issues in using computer simulations for facilitating collaborative learning.     

A distributed problem‐solving framework for probabilistic software effort estimation

Distributed problem‐solving (DPS) systems use a framework of human organizational notions and principles of intelligent systems to solve complex problems. Human organizational notions are used to decompose a complex problem into sub‐problems that can be solved using intelligent systems. The solutions of these sub‐problems are combined to solve the original complex problem. In this paper, we propose a DPS system for probabilistic estimation of software development effort. Using a real‐world software engineering dataset, we compare the performance of the DPS system with a neural network (NN) and show that the performance of the DPS system is equal to or better than that of the NN with the additional benefits of modularity, probabilistic estimates, greater interpretability, flexibility and capability to handle incomplete input data.     

The software architecture of a distributed problem‐solving environment

This paper describes the functionality and software architecture of a generic problem‐solving environment (PSE) for collaborative computational science and engineering. A PSE is designed to provide transparent access to heterogeneous distributed computing resources, and is intended to enhance research productivity by making it easier to construct, run, and analyze the results of computer simulations. Although implementation details are not discussed in depth, the role of software technologies such as CORBA, Java, and XML is outlined. An XML‐based component model is presented. The main features of a Visual Component Composition Environment for software development, and an Intelligent Resource Management System for scheduling components, are described. Some prototype implementations of PSE applications are also presented. Copyright © 2000 John Wiley & Sons, Ltd.     

Relationship between perceived problem‐solving skills and academic performance of novice learners in introductory programming courses

Past research has shown that student problem‐solving skills may be used to determine student final exam performance. This study reports on the relationship between student perceived problem‐solving skills 1 1 Henceforth, for brevity, we drop the word “perceived” in “student perceived problem‐solving skills” and use either “student perceived problem solving” or simply “student PSS.”
and academic performance in introductory programming, in formative and summative programming assessment tasks. We found that the more effective problem solvers achieved better final exam scores. There was no significant difference in formative assessment performances between effective and poor problem solvers. It is also possible to categorize students on the basis of problem‐solving skills, in order to exploit opportunities to improve learning around constructivist learning theory. Finally, our study identified transferability skills and the study may be extended to identify the impact of problem solving transfer skills on student problem solving for programming.     

A storyteller's guide to problem‐based learning for information systems management education

More than a decade ago, evidence‐based recommendations emerged regarding what students of information systems (IS) management education should learn and how should they learn it. Although these recommendations for how IS management should be taught remain valid, they need to be updated to account for recent advances in technologies that enable multimedia learning. Promoters of such technologies promise enhanced cognitive and behavioural outcomes, but this promise remains unreached, reflecting the underdeveloped multimedia‐enabled learning literature. To help attain this promise and rejuvenate the literature of multimedia learning, we offer a roadmap for new areas of research that would inform the design and use of a novel form of multimedia materials: narrative animated videos (NAVs). NAVs represent a form of self‐determined learning that features immersive, story‐based content. We argue that their use will intrinsically motivate users to process the materials to completion, thereby enhancing cognitive and behavioural outcomes, and thus catalysing the effectiveness of the team‐based learning and self‐regulated learning modes for problem‐based learning (PBL) delivery of IS management education. This compelling roadmap corresponds to meaningful IS research because it centres on a topic that the IS literature has long examined—the role of user motivation—and because its theoretical contributions invite specific paths of research for informing the design of the PBL delivery of IS management education within an information systems artefact.     

A flowchart‐based intelligent tutoring system for improving problem‐solving skills of novice programmers

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem‐solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one‐to‐one personalized and adaptive teaching. In this paper, a novel Flowchart‐based Intelligent Tutoring System (FITS) is proposed benefiting from Bayesian networks for the process of decision making so as to aid students in problem‐solving activities and learning computer programming. FITS not only takes full advantage of Bayesian networks, but also benefits from a multi‐agent system using an automatic text‐to‐flowchart conversion approach for engaging novice programmers in flowchart development with the aim of improving their problem‐solving skills. In the end, in order to investigate the efficacy of FITS in problem‐solving ability acquisition, a quasi‐experimental design was adopted by this research. According to the results, students in the FITS group experienced better improvement in their problem‐solving abilities than those in the control group. Moreover, with regard to the improvement of a user's problem‐solving ability, FITS has shown to be considerably effective for students with different levels of prior knowledge, especially for those with a lower level of prior knowledge.     

Leveraging legacy codes to distributed problem‐solving environments: a Web services approach

This paper presents WSOWG, a Web‐services‐oriented wrapper generator for automatically wrapping non‐networked legacy codes as Web services for reuse in distributed problem‐solving environments. Using WSOWG, a finite element based computational fluid dynamics (CFD) legacy code has been wrapped as a Web service. A problem‐solving environment for simulating incompressible Navier–Stokes flows has also been implemented. A user makes use of the CFD service through a Web page without knowing the exact implementation of the service. In this way, a user's computing environment can be extended to a heterogeneous distributed computing environment. Performance evaluation shows that the overhead to invoke the CFD Web service generated by WSOWG using Simple Object Access Protocol (SOAP) and CORBA Internet Inter‐ORB Protocol (IIOP) is reasonable compared with that of invoking another CFD Web service manually wrapped from the CFD legacy code using SOAP only. Copyright © 2004 John Wiley & Sons, Ltd.     

Learning adaptivity in support of flipped learning: An ontological problem‐solving approach

In recent years, flipped learning has received tremendous attention from educational practitioners and researchers. However, this study argues that existing e‐learning systems mainly serve for learning management and content delivery purposes, although they lack support for flipped learning. As an innovative educational approach, flipped learning requires more pedagogical elements, such as integrated instructional design and adaptive content delivery, to achieve effective direct instruction. This study aims to create a learning adaptivity design to support effective learning in the flipped individual learning space in which the teacher is absent. Because teaching involves various pedagogical and content knowledge sources, we propose a conceptual model of teaching as a function of the knowledge triad of Guideline (G), Teaching Activity (T), and Material (M). To realize this conceptualization, an ontological problem‐solving approach is used for knowledge‐based systems development to integrate the relevant knowledge sources. The knowledge model is created using the Protégé platform to develop OWL‐based domain ontology, task ontology, and SWRL‐based semantic rules to enable inference in the GTM triad for learning adaptivity. The case illustration shows that the knowledge‐based system prototype can adaptively guide student learning in the flipped individual learning space with the knowledge sources integrated.     

Self‐regulation during e‐learning: using behavioural evidence from navigation log files

The current paper examined the relationship between perceived characteristics of the learning environment in an e‐module in relation to test performance among a group of e‐learners. Using structural equation modelling, the relationship between these variables is further explored in terms of the proposed double mediation as outlined by Ning and Downing. These authors initially proposed that motivation and self‐regulation strategies are mediators between the perception of the learning environment and performance. In our replication and extension study, we substituted self‐reported self‐regulation with behavioural indicators of self‐regulation using navigation log files and focused on test‐taking rather than general motivation. We proposed that navigational patterns captured using log files can also help deduce self‐regulation in e‐modules and provide information in the absence of self‐reports. Path analyses provide partial support for our navigational hypotheses and the model. Implications of our results for the use of e‐module data and conclusions based on navigation are discussed.     

Student‐generated content in college teaching: content quality,behavioural pattern and learning performance

This study investigates the quality of course content, behavioural patterns of students and learning performance in teaching of student‐generated content (SGC). A total of 49 third‐year university students in educational technology participated in this study. By combining the methods of questionnaire, lag sequence analysis and interview, the study found that (1) SGC quality was acceptable, (2) SGC process has 14 significant behavioural sequences, and (3) students developed their knowledge and capability and were satisfied with SGC‐based teaching approach. In addition, this study revealed problems and proposed suggestions for SGC‐based course teaching. Finally, implications for course teaching in colleges, the limitations and future research plan were presented.     

Development and behavioral pattern analysis of a mobile guide system with augmented reality for painting appreciation instruction in an art museum

A mobile guide system that integrates art appreciation instruction with augmented reality (AR) was designed as an auxiliary tool for painting appreciation, and the learning performance of three groups of visiting participants was explored: AR-guided, audio-guided, and nonguided (i.e., without carrying auxiliary devices). The participants were 135 college students, and a quasi-experimental research design was employed. Several learning performance factors of the museum visitors aided with different guided modes were evaluated, including their learning effectiveness, flow experience, the amount of time spent focusing on the paintings, behavioral patterns, and attitude of using the guide systems. The results showed that compared to the audio- and nonguided participants, the AR guide effectively enhanced visitors' learning effectiveness, promoted their flow experience, and extended the amount of time the visitors spent focusing on the paintings. In addition, the visitors' behavioral patterns were dependent upon the guided mode that they used; the visitors who were the most engaged in the gallery experience were those who were using the AR guide. Most of the visitors using the mobile AR-guide system elicited positive responses and acceptance attitudes.     

Perceptions of learning effectiveness in M‐learning: scale development and student awareness

The purpose of this study is to develop a multi‐dimensional scale to measure students' awareness of key competencies for M‐learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical thinking and problem solving, and communication. The research subjects are 815 students from the elementary school that participate in M‐learning programme in Taiwan. The research results show that students have better self‐awareness in team collaboration and creative thinking, but have worse self‐awareness in critical thinking and problem solving. This study also found that there was no significant difference between genders in the KCMLS, but students who study in the schools that committed in M‐learning longer have higher awareness in all dimensions than students who study in the schools that committed to M‐learning in fewer years.     

A-Brain: a general system for solving data analysis problems

An intelligent system should be able to solve a wide range of problems from different domains. In this paper we propose a complex and adaptive system capable of solving various data analysis problems without needing human help for parameter settings. The system, called A-Brain, consists of several interconnected components (a decision-maker, a trainer, and several problem solvers) which provide a base for building complex problem solvers. The parameters of the trainer's algorithm are problem independent. This fact is a requirement for intelligent systems which cannot rely on human intervention while operating. The A-Brain system is used to solve some well-known problems in the field of symbolic regression and classification. Numerical experiments show that the A-Brain system is able to perform very well on the considered test problems.     

一种基于序列模式挖掘的独居老人用电预警模型

随着人口老龄化的加深,独居老人数量快速增长,如何及时检测发现老人出现异常情况成为小区管理的迫切需求。另一方面,智能电表技术的发展让用电数据的采集更加精确和及时,使得实时检测老人用电数据异常成为可能,但如何对此海量用电数据进行分析成为了难点。为此,本文提出了一种基于序列模式挖掘的独居老人用电数据预警模型,从历史数据中挖掘了老人用电特征的共性和特性,同时综合考虑了时间、天气数据等外部因素,通过深度学习进行异常检测。相比传统的检测方法,本文提出的模型能更加快速准确地检测异常,为独居老人的生活提供了安全保障,显著降低了社区管理人员的压力。在真实数据集上的实验结果验证了该模型的有效性。     

Developing an effective support system for inquiry learning in a Web-based environment

Abstract Sixty-five teams of basic and secondary school students solved problem-solving tasks during a virtual hike in a Web-based inquiry-learning simulation 'Hiking Across Estonia'. This environment provided learners with all necessary background information for problem-solving and tools for carrying out experiments. There were 25 tasks in certain order about ecological and environmental issues. The teams were clustered according to the data about participants, the results of the pre- and post-test, and their achievement in problem-solving tasks of the virtual hike. Only two out of five clusters were regarded as effective in solving problems and analysing tables, graphs, figures, and photos. The others had difficulties in forming contextual or task and process awareness. A support system for increasing the effectiveness of inquiry learning and enhancing their development of analytical skills was developed on the basis of the strategies that the members of five clusters had used in solving the problems, their achievement in solving the tasks during the virtual hike and in the pre- and post-test, and the personal data about the teams. The support system contained different notes before solving the problems and changed sequence of the tasks on the virtual hike for some clusters. The usage of this system was evaluated in a second study with 60 teams. The comparison of two studies demonstrated significant effectiveness of the support system to both general problem-solving ability and analytical skills. The characteristics of each cluster and the influence of the support system are discussed in this paper.     

The influences of a two-tier test strategy on student learning: A lag sequential analysis approach

Recently, programming skills have become a core competence. Many teaching strategies were developed to improve programming skills. Among them, online tests were widely applied to enhance students learning. Nonetheless, they may not be able to engage students in deep thinking and reflections. Thus, a two-tier test strategy was proposed to address this issue. However, previous research mainly focused on investigating the effectiveness of the two-tier test strategy but there is a lack of studies that investigate why the two-tier test approach is effective. To this end, we developed an online test, where the two-tier test strategy was implemented. Additionally, an empirical study was conducted to explore the influences of the two-tier test approach on students' learning performance and behavior patterns. Pre-test and post-test scores were applied to assess students' learning performance while a lag sequential analysis was used to analyze behavior patterns. Regarding learning performance, the proposed two-tier test can improve students' programming skills. Regarding behavior patterns, the two-tier test approach facilitates students to develop a learning by reviewing strategy, which is useful to improve their programming skills.     

Creating user‐generated content for location‐based learning: an authoring framework

Two recent emerging trends are that of Web 2.0, where users actively create content and publish it on the Web, and also location awareness, where a digital device utilizes a person's physical location as the context to provide specific services and/or information. This paper examines how these two phenomena can be brought together so that user‐generated content on mobile devices is used to provide informal learning opportunities relevant to a person's location. However, the generative process of such media does not always have much guidance on how or what to create, so the quality of such information can be highly variable. To overcome this, a framework has been designed to guide the authoring of user‐generated content so that it can be used for informal learning about one's immediate surroundings (particularly in an outdoor setting), combining pedagogical aspects with those from human–computer interaction and environmental aesthetics. The framework consists of six dimensions that include aspects such as curriculum area (e.g. science, art), type of communication, use of language/media related to the landscape, knowledge level of content, contextual aspects, and types of interaction. In order to test the framework before it could be used to scaffold new content, it was first used to analyse and evaluate over 200 items of existing user‐generated content, to investigate the appropriateness of the proposed dimensions and the items contained therein or if any were missing. This paper presents the findings of this initial testing phase, together with a discussion of how the framework can be improved, in order to help scaffold the creation of new user‐generated content in the future.