Dynamics of cognitive load theory: A model-based approach

Since its conception nearly two decades ago, cognitive load theory (CLT) has been a fertile ground for both empirical and theoretical investigations. The research accumulated over the years has contributed not only to the theory’s validation, but also generated new insights. These new insights helped to refine CLT, making it more precise, but also more complex. A formal (mathematical) simulation model is proposed as a new analytical tool for investigating CLT’s increasingly intricate postulates and their dynamic implications. This paper describes how the theoretical relationships between certain features of instruction and the cognitive capacities of learners can be expressed formally, and how the resulting model can help gain insights into the learning dynamics that arise from these relationships, providing a new aid for research, teaching and practice in the field of instructional design.     

Progression of mental models throughout the phases of a computer-based instructional simulation: Supportive information,practice, and performance

Students of chemical engineering (n = 26) participated in an experiment using a computer-based simulation of a chemical plant. The progression of participants’ mental models was examined throughout a computer-based instructional experience as they acquired the complex cognitive skills of troubleshooting. Participants’ mental models of the complex learning task were matched against an expert mental model at five observation points through the instruction. Progressions of learners’ mental models were examined before and after three phases of the instructional process: supportive information presentation, problem solving practice, and performance test. The results indicated a significant change in participants’ mental models after receiving the supportive information and little change after practice or performance. This paper presents the results of this investigation and discusses the findings and their implications for computer-based instruction and training.     

Automatic text categorization based on content analysis with cognitive situation models

Text categorization is an important research area of text mining. The original purpose of text categorization is to recognize, understand and organize different types of texts or documents. The general categorization approaches are treated as supervised learning, which infers similarity among a collection of categorized texts for training purposes. The existing categorization approaches are obviously not content-oriented and constrained at single word level.This paper introduces an innovative content-oriented text categorization approach named as CogCate. Inspired by cognitive situation models, CogCate exploits a human cognitive procedure in categorizing texts. In addition to traditional statistical analysis at word level, CogCate also applies lexical/semantical analysis, which ensures the accuracy of categorization. The evaluation experiments have testified the performance of CogCate. Meanwhile, CogCate remarkably reduces the time and effort spent on software training and maintenance of text collections. Our research work attests that interdisciplinary research efforts benefit text categorization.     

分布共享存贮器型MPP系统原理和实现方法

在两类并行计算机系统中,分布式存贮器(DM)型比共享存贮器(SM)型性能优越,但用户开发软件难度特别大。本文详细地介绍了用软件的方法将一个物理上的DM系统构成一个逻辑上的SM系统,即分布共享存贮器(DSM)系统的原理和实现方法。     

Perspectives on computer aiding in cognitive work domains: toward predictions of effectiveness and use

A two-stage process is proposed for evaluating computer aiding in cognitive work domains. The first stage relies on a taxonomic framework that facilitates assessments regarding the relative strengths and weaknesses of humans and computers for different computer-aiding schemes. The second stage introduces the construct of tension, which addresses the potential implications of the interplay between computer aiding constraints and human tendencies. This approach is intended to provide designers, analysts and managers with greater insight into the nature of computer aiding and ultimately to enhance their ability to predict its effectiveness as well as its prospects for being used.     

Mental models and computer modelling

Abstract This paper is concerned with the place of mental models in the process of knowledge construction and in particular, the relationship between mental models and computer models in that process. It identifies what is meant by mental models and outlines why they might be seen to be central to the process of acquiring knowledge. In this context, the second part of the paper analyses and discusses children's use of a spreadsheet to build their own computer models. It is suggested that the process of building models on a computer may provide direct support to the cognitive processes of constructing mental models, although the relationship is not straight forward.     

The Society's Lecture 1987 The Use of Models in Human-Computer Interface Design

A user-centred approach to human-computer interface design requires that the designer has appropriate tools to aid in the design process and employs iterative design procedures which incorporate user evaluations. The concept of using models of the user as an interface design tool is discussed, and several approaches to user modelling are described. These approaches are divided into the broad categories of conceptual and quantitative models. Conceptual models deal primarily with representations of users1 cognitive processes, structures and strategies. Quantitative models include performance, ergonomic, computer simulation and statistical models. Examples of both a conceptual and a quantitative model are provided to illustrate human-computer interface design implications. Some unresolved issues pertaining to both categories of models are discussed, and recommendations are made to improve modelling as an interface design tool.     

FACETS: A cognitive business intelligence system

A cognitive decision support system called FACETS was developed and evaluated based on the situation retrieval (SR) model. The aim of FACETS is to provide decision makers cognitive decision support in ill-structured decision situations. The design and development of FACETS includes novel concepts, models, algorithms and system architecture, such as ontology and experience representation, situation awareness parsing, data warehouse query construction and guided situation presentation. The experiments showed that FACETS is able to play a significant role in supporting ill-structured decision making through developing and enriching situation awareness.     

Computer use in older adults: Determinants and the relationship with cognitive change over a 6 year episode

Cognitively challenging activities may support the mental abilities of older adults. The use of computers and the Internet provides divergent cognitive challenges to older persons, and in previous studies, positive effects of computer and Internet use on the quality of life have been demonstrated. The present study addresses two research aims regarding predictors of computer use and the relationship between computer use and changes in cognitive abilities over a 6-year period in both younger (24-49 years) and older adults (older than 50 years). Data were obtained from an ongoing study into cognitive aging: the Maastricht Aging Study, involving 1823 normal aging adults who were followed for 9 years. The results showed age-related differences in predictors of computer use: the only predictor in younger participants was level of education, while in older participants computer use was also predicted by age, sex and feelings of loneliness. Protective effects of computer use were found for measures of selective attention and memory, in both older and younger participants. Effect sizes were small, which suggests that promotion of computer activities in older adults to prevent cognitive decline may not be an efficient strategy.     

Development of a computer game-based framework for cognitive behaviour identification by using Bayesian inference methods

In this work a novel technique for cognitive behavioural data acquisition via computer/console games is introduced by which the user feels more relax than s/he is in a formal environment (e.g., labs and clinics) and has less disruption as s/he provides cognitive data sequence by playing a game. The method can be adapted into any game and is based on the assumption that in this way more efficient analysis of mind can be made to unveil the cognitive or mental characteristics of an individual. In experiments of the proposed work a commercial console game was utilised by different users to complete the tasks in which each game player followed his/her own optional scenarios of the game for a certain period of time. The attributes were then extracted from the behavioural video data sequence by visual inspection where each one corresponds to user’s behavioural characteristics spotted throughout the game and then analysed by the Bayesian network utility. At the end of all the experiments, two types of results were obtained: semantic representation of behavioural attributes and classification of personal behavioural characteristics. The approach is proved to be a unique way and helped identify general and specific behavioural characteristics of the individuals and is likely to open new areas of applications.     

Representational congruence and information retrieval: Towards an extended model of cognitive fit

The theory of cognitive fit suggests that a match between the problem representation and the task results in a better problem solving performance. In this paper, we extend the concept of cognitive fit to also account for the congruence between the external information and the internal representation of the user. This representational congruence and its effect on information retrieval are tested in an experimental setting. Subjects who are assigned to either of the two models of external representation (propositional networks, PNs, and object-oriented, OO) are provided domain-based information. A computer program, OBJECT_IMAGE, is used to measure the reaction times and error rates of subjects on different attributes such as inheritance, message passing, and changing dynamics. The results favor the existence of OO-like features to attain cognitive economy in human information processing.     

共享适应度粒子群在双机ETV中的应用

针对机场货运区双机双货位升降式转运车（ETV）并行工作时任务链生成困难的问题,提出一种基于ETV载物台的任务链生成算法。该算法结构清晰,且易于计算总运行时间。针对粒子群算法在计算双机ETV最优任务序列时易出现早熟问题,提出改进的共享适应度粒子群算法。该算法在混沌粒子群算法的基础上融合共享适应度的思想,当混沌粒子群算法的全局最优解趋于稳定时,选取百分之二十的粒子留守共享半径内,其他粒子重新初始化并继续迭代。实验仿真结果表明和标准粒子群算法、混沌优化粒子群算法相比,共享适应度粒子群算法可以有效地避免早熟,全局寻优能力更强,得到的结果更优且更稳定。     

On the Expressiveness of Timed Coordination via Shared Dataspaces

Since Linda, many differents coordination models using shared dataspaces have been developped. However, a few only have incorporated the notion of time. This paper builds upon previous work to study the expressive power of two families of timed coordination models based on shared dataspaces. The first one relies on Linda's communication primitives whereas the second relies on the more general notion of multi-set rewriting, incorporated, for instance, in Gamma. We analyse the expressiveness increase provided by the primitives in each of the two families and also compare the expressiveness power of the two families.     

AI models of verbal/conceptual analogy

This article surveys some psychological research on analogy and the theoretical notions that it spawned, which in turn have served as some of the foundationalnotions in AI models. A number of AI models of analogy are described. It is argued that future efforts could be based on the integration of the key insights of the models. This includes the incorporation of contextual information, the construction of dynamic semantic bases, the incorporation of multiple approaches to the problem of inference generation and constraint, and the construction of systems that can be used as test beds or tool kits for the analysis of representational and inference schemes. Along with the prospects, there are also pointers to the lingering issues.     

Taking fun seriously: Using cognitive models to reason about interaction with computer games

This paper seeks to extend the application of techniques from affective psychology to show how cognitive models can be used to represent and reason about interaction with computer games. It is argued that this modelling activity provides insights into the motivational appeal that often distinguishes computer games from other forms of human computer interaction. The long-term aim behind this research is to use our improved understanding of interaction with computer games to inform the subsequent development of more general classes of interactive systems. Barnard's Interacting Cognitive Subsystems (ICS) is used throughout this paper. This decision is justified by the fact that ICS has already been applied to analyse the negative emotions surrounding clinical depression. This previous work provides a useful starting point for our investigation of the more positive emotions evoked during interaction with computer games. A further justification is that ICS has also been successfully used to represent and reason about the design of human computer interfaces.     

Assessing the influence of import-coupling on OCL expression maintainability: A cognitive theory-based perspective

The aim of this paper is to present the definition of the measures for the import-coupling of OCL expressions, along with the empirical validation of these as early indicators of the maintainability of OCL expressions. This empirical validation has been carried out by means of an experiment and its replica, conducted with undergraduate students of Spanish and Argentinean universities, respectively. To perform this experimental activity, we have followed a cognitive theory-based approach, since the understanding of the cognitive demands that OCL expressions place on software engineers will allow us to examine in greater depth the real influence of import-coupling on the maintainability of OCL expressions. The empirical results, obtained through the analysis of the data from the experiment and its replica, first of all separately and then together after a meta-analysis study, reveal evidence suggesting that import-coupling exerts a certain amount of influence on the comprehensibility and modifiability of OCL expressions. The measures that have most influence on OCL expression comprehensibility are those related to problem objects (Number of Navigated Relationships (NNR), Weighted Number of Navigations (WNN), Depth of Navigations (DN) and Number of Attributes referred through Navigations (NAN)), relationships between problem objects (Number of Navigated Classes (NNC) and Number of Explicit Iterator variables (NEI)), as well as reified objects (Weighted Number of Collections Operations (WNCO)). On the other hand, it is only measures related to relationships between problem objects that are the main influence on OCL expression modifiability. The influence of import-coupling on the comprehensibility and modifiability of OCL expressions was reaffirmed through the cognitive complexity (i.e. we show that import-coupling affects the cognitive complexity and that the latter influences the comprehension and modification of OCL expressions). These results may have educational implications, apart from what they might mean for practitioners in the industry, as is explained in the conclusions.     

Solving macroeconomic models with “off-the-shelf” software: An example of potential pitfalls

When working with large-scale models or numerous small models, there can be a temptation to rely on default settings in proprietary software to derive solutions to the model. In this paper we show that, for the solution of non-linear dynamic models, this approach can be inappropriate. Alternative linear and non-linear specifications of a particular model are examined. One version of the model, expressed in levels, is highly non-linear. A second version of the model, expressed in logarithms, is linear. The dynamic solution of each model version has a combination of stable and unstable eigenvalues so that any dynamic solution requires the calculation of appropriate “jumps” in endogenous variables. We can derive a closed-form solution of the model, which we use as our “true” benchmark, for comparison with computational solutions of both linear and non-linear models. Our approach is to compare the “goodness of fit” of reverse-shooting solutions for both the linear and non-linear model, by comparing the computational solutions with the benchmark solution. Under the basic solution method with default settings, we show that there is significant difference between the computational solution for the non-linear model and the benchmark closed-form solution. We show that this result can be substantially improved using modifications to the solver and to parameter settings.     

共享服务模式下WEB框架的设计与应用

本文将研究一种共享式服务框架（SSF）。SSF运用MVC理论，基于struts成熟框架模型提供框架的二次封装。它使公共组件模块化，提供统一的调用接口，使用xml对上层模块进行配置，实现软件开发的松耦合。与此同时，使标准的web风格的共享，提高表示层的可重用性．缩短了软件的开发周期。