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 problem solving oriented intelligent tutoring system to improve students' acquisition of basic computer skills

Personalization and intelligent tutor are two key factors in the research on learning environment. Intelligent tutoring system (ITS), which can imitate the human teachers' actions to implement one-to-one personalized teaching to some extent, is an effective tool for training the ability of problem solving. This research firstly discusses the concepts and methods of designing problem solving oriented ITS, and then develops the current iTutor based on the extended model of ITS. At last, the research adopts a quasi-experimental design to investigate the effectiveness of iTutor in skills acquisition. The results indicate that students in iTutor group experience better learning effectiveness than those in the control group. iTutor is found to be effective in improving the learning effectiveness of students with low-level prior knowledge.     

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.     

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.     

基于情感识别的智能教学系统研究

针对传统的智能教学系统(ITS)在情感方面的缺失,提出了基于情感识别技术的ITS模型.该系统模型在传统的教学系统上新增情感识别模块,利用人脸表情识别以及文本识别等技术所构建,可以获取和识别学生的学习情感,并根据学习情感进行相应的情感激励策略,实现情感化的教学.     

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.     

Students' mathematics word problem‐solving achievement in a computer‐based story

The purpose of this study was to investigate the effect of a computer‐based story, which was designed in anchored instruction framework, on sixth‐grade students' mathematics word problem‐solving achievement. Problems were embedded in a story presented on a computer as computer story, and then compared with the paper‐based version of the same story and to a condition that presented the problems as typical, isolated word problems (i.e., a non‐story condition including only problems). One hundred twenty‐eight sixth‐grade students from two public middle schools in Turkey participated in this study. In a pretest–posttest experimental design, students were randomly assigned to one of the treatment groups mentioned earlier in which they solved the same mathematics word problems. A one‐way analysis of covariance was used to analyse students' achievement in the treatment groups. The results indicated that students who solved the problems in the computer story treatment had significantly higher achievement scores than students who solved the problems in the paper story and isolated word problems treatments. In addition, the story was found to be significantly more effective than the non‐story treatment when it was presented on computer.     

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.     

Supporting skill integration in an intelligent tutoring system for code tracing

Background

Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited.

Objectives

The current work presents the development and empirical evaluation of instructional design targeting students' difficulties in code tracing particularly in integrating component skills in the Trace Table Tutor (T3), an intelligent tutoring system.

Methods

Beyond the instructional features of active learning, step-level support, and individualized problem selection of intelligent tutoring systems (ITS), the instructional design of T3 (e.g., hints, problem types, problem selection) was optimized to target skill integration based on a domain model where integrative skills were represented as combinations of component skills. We conducted an experimental study in a university-level introductory Python programming course and obtained three findings.

Results and Conclusions

First, the instructional features of the ITS technology support effective learning of code tracing, as evidenced by significant learning gains (medium-to-large effect sizes). Second, performance data supports the existence of integrative skills beyond component skills. Third, an instructional design focused on integrative skills yields learning benefits beyond a design without such focus, such as improving performance efficiency (medium-to-large effect sizes).

Major Takeaways

Our work demonstrates the value of designing for skill integration in learning technologies and the effectiveness of the ITS technology for computing education, as well as provides general implications for designing learning technologies to foster robust learning.     

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.     

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.     

A conversational intelligent tutoring system to automatically predict learning styles

This paper proposes a generic methodology and architecture for developing a novel conversational intelligent tutoring system (CITS) called Oscar that leads a tutoring conversation and dynamically predicts and adapts to a student’s learning style. Oscar aims to mimic a human tutor by implicitly modelling the learning style during tutoring, and personalising the tutorial to boost confidence and improve the effectiveness of the learning experience. Learners can intuitively explore and discuss topics in natural language, helping to establish a deeper understanding of the topic. The Oscar CITS methodology and architecture are independent of the learning styles model and tutoring subject domain. Oscar CITS was implemented using the Index of Learning Styles (ILS) model (Felder & Silverman, 1988) to deliver an SQL tutorial. Empirical studies involving real students have validated the prediction of learning styles in a real-world teaching/learning environment. The results showed that all learning styles in the ILS model were successfully predicted from a natural language tutoring conversation, with an accuracy of 61–100%. Participants also found Oscar’s tutoring helpful and achieved an average learning gain of 13%.     

A multi‐layered architecture for managing graphical interfaces and tutoring mixed‐strategy dialogues

This paper describes a tool set that allows a courseware author to design a student interface. These tools produce systems dedicated to intelligent computer aided learning, with a better balance between planned tutoring and free‐exploration of micro‐worlds. Mixing these two approaches leads to a distinction between the pedagogical objectives and the presentation elements. Reactive graphical interfaces are better suited to develop micro‐worlds, while the tutoring relies on pedagogical strategies. Then, a multi‐layered architecture is designed in order to use such a graphical student interface under the control of teaching strategies and intentional dialogues. Tutoring rules drive these dialogues by combining several types of functions: predefined strategies, interaction management primitives and pedagogical tactics. These functions are means to articulate the reactive and graphical level with the logical and intentional one. Copyright © 1999 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.     

Students' usability evaluation of a Web‐based tutorial program for college biology problem solving

The understanding of core concepts and processes of science in solving problems is important to successful learning in biology. We have designed and developed a Web‐based, self‐directed tutorial program, SOLVEIT, that provides various scaffolds (e.g., prompts, expert models, visual guidance) to help college students enhance their skills and abilities in solving problems in science. An initial version of SOLVEIT was used in this study. This paper details the features of SOLVEIT that are contextualized within the biological domains of evolution and ecology. A qualitative case study was conducted to evaluate the usability of the program. Selected students were recruited from an introductory biology course at a large public university in the south‐eastern United States. Data for this study were collected through the SOLVEIT database and semi‐structured interviews. The findings of this study demonstrate the potential of the program for improving students' problem solving in biology. Suggestions for the use of SOLVEIT and its further improvement and development are discussed, along with suggestions for future research. This study also provides more general guidance for researchers and practitioners who are interested in the design, development and evaluation of Web‐based tutorial programs in science education.     

Mobile guide system using problem‐solving strategy for museum learning: a sequential learning behavioural pattern analysis

Mobile devices have been increasingly utilized in informal learning because of their high degree of portability; mobile guide systems (or electronic guidebooks) have also been adopted in museum learning, including those that combine learning strategies and the general audio–visual guide systems. To gain a deeper understanding of the features and limitations of these guide systems in a museum‐learning context and also to provide new designs that better guide learners in interacting with peers and exhibitions, in‐depth exploration of learners' actual visits and analyses of their behavioural patterns is crucial. This study was based on empirical observation and analysis of the learning behaviours (recorded on video) of 65 elementary‐school students who were placed into three groups: mobile guide with problem‐solving strategy, audio–visual mobile guide and paper‐based learning‐sheet guide. By coding and analysing the video and conducting sequential analysis and frequency analysis of learning‐related discussion content, behavioural interaction patterns were determined by which the features and limitations of the different types of guides were compared. Among the findings, it was discovered that the students in the problem‐solving mobile guide group showed a higher level of two‐way interactions with their peers and the exhibits, as well as more learning‐related discussions. Relevant suggestions for teachers, researchers and guide‐systems developers are also given.     

Automatic estimation of exercises' difficulty levels in a tutoring system for teaching the conversion of natural language into first‐order logic

The estimation of the difficulty level of exercises is a fundamental aspect of intelligent tutoring systems, and it is necessary in order to achieve better adaptation to the students' needs and maximize learning efficiency. In this article, we present an approach to automatically estimates the difficulty level of exercises in natural language (NL) to first‐order of logic (FOL). The estimation of an exercise's difficulty level is based on the complexity of the corresponding answer, that is the FOL formula, as well as the structure and the semantics of the exercise, that is a natural language sentence and it is carried out in two main steps. Initially, a preliminary estimation is performed based on the complexity of the FOL formula. The system takes as input parameters the number, the type and the order of quantifiers, the number of implications, and the number of different connectives. Afterwards, the final estimation is made based on both semantic aspects of the NL sentence and the structure of the FOL formula. An evaluation study was conducted to assess the system's performance, and the results are very encouraging.     

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 service‐based runtime environment for native applications

Unlike interpreted application programs that run within the rich runtime environment of their own interpreters, natively compiled application programs are typically thought of as executing on the barebones runtime environment provided by their own operating systems and dynamic linkers. This article presents the notion of a service‐based runtime (SBRT) environment for natively compiled application programs, in which the current dynamic linker is only a core service and other extensive middleware‐type services are available to the running application program. It then describes a dynamic‐linker‐based implementation of such an environment, called dlSBRT. dlSBRT implements a unified interface that allows it to be extensible by means of extension dynamic services. Implemented examples of such services are presented and the performance of dlSBRT, when such example services are deployed, is evaluated. Copyright © 2009 John Wiley & Sons, Ltd.