Kamran Sedig

Role of interface manipulation style and scaffolding on cognition and concept learning in learnware

This research investigates the role of interface manipulation style on reflective cognition and concept learning through a comparison of the effectiveness of three verisons of a software application for learning two-dimensional transformation geometry. The three versions respectively utilize a Direct Object Manipulation (DOM) interface in which the user manipulates the visual representation of objects being transformed; a Direct Concept Manipulation (DCM) interface in which the user manipulates the visual representation of the transformation being applied to the object; and a Reflective Direct Concept Manipulation (RDCM) interface in which the DCM approach is extended with scaffolding. Empirical results of a study showed that grade-6 students using the RDCM version learned significantly more than those using the DCM version, who is turn learned significantly more than those using the DOM version. Students using the RDCM version had to process information consciously and think harder than those using the DCM and DOM versions. Despite the relative difficulty when using the RDCM interface style, all three groups expressed a similar (positive) level of liking for the software. This research suggests that some of the educational deficiencies of Direct Manipulation (DM) interfaces are not necessarily caused by their “directness,” but by what they are directed at—in this case directness toward objects rather than embedded educational concepts being learned. This paper furthers our understanding of how the DM metaphor can be used in learning- and knowledge-centered software (i.e., learnware) by proposing a new DM metaphor (i.e., DCM), and the incorporation of scaffolding to enhance the DCM approach to promote reflective cognition and deep learning.

Characterizing interaction with visual mathematical representations.

This paper presents a characterization of computer-based interactions by which learners can explore and investigate visual mathematical representations (VMRs). VMRs (e.g., geometric structures, graphs, and diagrams) refer to graphical representations that visually encode properties and relationships of mathematical structures and concepts. Currently, most mathematical tools provide methods by which a learner can interact with these representations. Interaction, in such cases, mediates between the VMR and the thinking, reasoning, and intentions of the learner, and is often intended to support the cognitive tasks that the learner may want to perform on or with the representation. This paper brings together a diverse set of interaction techniques and categorizes and describes them according to their common characteristics, goals, intended benefits, and features. In this way, this paper aims to provide a preliminary framework to help designers of mathematical cognitive tools in their selection and analysis of different interaction techniques as well as to foster the design of more innovative interactive mathematical tools. An effort is made to demonstrate how the different interaction techniques developed in the context of other disciplines (e.g., information visualization) can support a diverse set of mathematical tasks and activities involving VMRs.

Designing interfaces that support formation of cognitive maps of transitional processes: an empirical study

Many conditions, phenomena, and concepts are of a transitional nature. Transitional processes involve change from one form to another, such as biological, chemical, and geological metamorphoses. Transitional processes take place in time-space and are not always easy to encode, communicate, and understand. The purpose of this research is to investigate how to design human-computer interfaces that support users in their formation of cognitive maps of transitional processes. To conduct this investigation, geometric shapes were used as the testbed, and their metamorphic transformations were captured and communicated using three different interface styles: temporally stacked, spatially distributed, and spatio-temporal. The usability and effectiveness of each interface was evaluated. The results of the study indicate that the spatio-temporal interface is the most effective of the three interfaces. The findings of this research imply that many kinds of transitional processes, such as rock metamorphoses, historical changes, or economical processes, may best be explored and understood using spatio-temporal interfaces.

Application of Information Visualization Techniques to the Design of a Mathematical Mindtool: A Usability Study

One of the goals of information visualization is to support human thinking through the use of external visual aids. Mathematical mindtools can act as visual cognitive aids to enhance thinking and reasoning about mathematical objects and concepts. Although some mathematical mindtools incorporate information visualization techniques, the systematic use of these techniques in the design of these tools and their effect on users’ thinking and reasoning need to be investigated. A mathematical mindtool called PARSE (Platonic-Archimedean Solids Explorer) is presented in this paper. PARSE is intended to support the exploration and learning of a subset of geometric shapes. The mathematical objects and concepts embedded in PARSE have been enhanced using information visualization techniques. A usability study of PARSE and its information visualization techniques have been conducted and reported. The study shows that information visualization techniques enhance and support learning and exploration of mathematical concepts. The findings reported in this paper suggest that mathematical mindtools provide a fertile ground for investigating different information visualization techniques and their effectiveness in supporting learning tasks.

The Challenge of Big Data in Public Health: An Opportunity for Visual Analytics

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data’s volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

Toward operationalization of 'flow' in mathematics learnware

Many children are not motivated to learn mathematics. Flow, a type of intrinsic motivation, has been described as an optimal experience in which a learner can derive great joy from a learning activity. This paper examines the importance and application of flow while learning mathematics. An operational model of flow for designing childrens mathematics learnware is proposed. This model is intended to operationalize the characteristics of flow in mathematics learnware in an integrated manner, facilitating the flow experience for children. The suitability of the model is demonstrated through an instantiated operational learnware called Super Tangrams. Super Tangrams aims to facilitate childrens understanding of transformation geometry while making the learning activity enjoyable and a flow experience. A study is reported that evaluates if the operational instance of the model promotes the flow experience while learning mathematics. The results suggest that the model is highly effective.

Human-Centered Interactivity of Visualization Tools: Micro- and Macro-level Considerations

Visualization tools can support and enhance the performance of complex cognitive activities such as sense making, problem solving, and analytical reasoning. To do so effectively, however, a human-centered approach to their design and evaluation is required. One way to make visualization tools human-centered is to make them interactive. Although interaction allows a user to adjust the features of the tool to suit his or her cognitive and contextual needs, it is the quality of interaction that largely determines how well complex cognitive activities are supported. In this chapter, interactivity is conceptualized as the quality of interaction. As interactivity is a broad and complex construct, we categorize it into two levels: micro and macro. Interactivity at the micro level emerges from the structural elements of individual interactions. Interactivity at the macro level emerges from the combination, sequencing, and aggregate properties and relationships of interactions as a user performs an activity. Twelve micro-level interactivity elements and five macro-level interactivity factors are identified and characterized. The framework presented in this chapter can provide some structure and facilitate a systematic approach to design and evaluation of interactivity in human-centered visualization tools.

Adjustable properties of visual representations: Improving the quality of human-information interaction

Complex cognitive activities, such as analytical reasoning, problem solving, and sense making, are often performed through the mediation of interactive computational tools. Examples include visual analytics, decision support, and educational tools. Through interaction with visual representations of information at the visual interface of these tools, a joint, coordinated cognitive system is formed. This partnership results in a number of relational properties—those depending on both humans and tools—that researchers and designers must be aware of if such tools are to effectively support the performance of complex cognitive activities. This article presents 10 properties of interactive visual representations that are essential and relational and whose values can be adjusted through interaction. By adjusting the values of these properties, better coordination between humans and tools can be effected, leading to higher quality performance of complex cognitive activities. This article examines how the values of these properties affect cognitive processing and visual reasoning and demonstrates the necessity of making their values adjustable—all of which is situated within a broader theoretical framework concerned with human‐information interaction in complex cognitive activities. This framework can facilitate systematic research, design, and evaluation in numerous fields including information visualization, health informatics, visual analytics, and educational technology.

Characterizing navigation in interactive learning environments

Interactive learning environments (ILEs) are increasingly used to support and enhance instruction and learning experiences. ILEs maintain and display information, allowing learners to interact with this information. One important method of interacting with information is navigation. Often, learners are required to navigate through the information space of an ILE, a process which can be quite difficult and cognitively exacting as the information space becomes very large and complex. Proper design can make this process less exacting and, at the same time, facilitate better learning of the information space. However, this is not easy to do, especially for ILEs. Frameworks can assist in the effective analysis and design of interactive environments. However, there is lack of conceptual frameworks for guiding the analysis and design of navigation in ILEs. This paper tries to address this issue by presenting a framework which can be used to characterize navigation within ILEs. To create this framework, this paper brings together research from various disciplines, such as human-computer interaction design, educational multimedia design, cognitive technologies and learning sciences. This framework prescribes a three-stage process for designing and analyzing navigation: 1. content structuring; 2. information navigation modeling; 3. interface presentation structuring. By bringing these three stages together, it is intended to provide a conceptual framework to assist and guide designers in the proper analysis and design of navigation in ILEs.

Distribution of Information Processing While Performing Complex Cognitive Activities with Visualization Tools

When using visualization tools to perform complex cognitive activities, such as sense-making, analytical reasoning, and learning, human users and visualization tools form a joint cognitive system. Through processing and transfer of information within and among the components of this system, complex problems are solved, complex decisions are made, and complex cognitive processes emerge—all in a manner that would not be easily performable by the human or the visualization tool alone. Although researchers have recognized this, no systematic treatment of how to best distribute the information-processing load during the performance of complex cognitive activities is available in the existing literature. While previous research has identified some relevant principles that shed light on this issue, the pertinent research findings are not integrated into coherent models and frameworks, and are scattered across many disciplines, such as cognitive psychology, educational psychology, information visualization, data analytics, and computer science. This chapter provides an initial examination of this issue by identifying and discussing some key concerns, integrating some fundamental concepts, and highlighting some current research gaps that require future study. The issues examined in this chapter are of importance to many domains, including visual analytics, data and information visualization, human-information interaction, educational and cognitive technologies, and human-computer interaction design. The approach taken in this chapter is human-centered, focusing on the distribution of information processing with the ultimate purpose of supporting the complex cognitive activities of human users of visualization tools.