Designing information visualization for higher education institutions: A pre-design study

The multidimensional of students’ data and the limitations of the currently-used data management tools in higher education institutions (HEIs) have been identified as causes of constrained decision-making process in the domain.This, therefore, necessitates a pre-design study for the HEI students’ datafocused InfoVis.The objectives of this study are to identify the prevailing practices of HEI data management, the data analytics methods that are generally employed by HEI data analysts and the comprehensive dimensions that are related to HEI students and adequate for conveying the domain explicit knowledge preferences. A mixed method approach with survey questionnaire and interview as data collection methods, is used.The contributions of this study, among others, are: (i) identification of the pattern and relationship of the domains explicit knowledge preferences; and (ii) the elicitation and description of students’ data dimensions.These are expected to form the basis for the choice and implementation of the content delivery techniques in designing the domain-focused InfoVis.Our future works therefore entail developing the HEI InfoVis conceptual framework, designing the HEI students’ data-focused InfoVis and conducting its users’ experimental evaluation

Conceptual design framework for information visualization to support multidimensional datasets in higher education institutions

Information Visualization (InfoVis) enjoys diverse adoption and applicability because of its strength in solving the problem of information overload inherent in institutional data. Policy and decision makers of higher education institutions (HEIs) are also experiencing information overload while interacting with students‟ data, because of its multidimensionality. This constraints decision making processes, and therefore requires a domain-specific InfoVis conceptual design framework which will birth the domain‟s InfoVis tool. This study therefore aims to design HEI Students‟ data-focused InfoVis (HSDI) conceptual design framework which addresses the content delivery techniques and the systematic processes in actualizing the domain specific InfoVis. The study involved four phases: 1) a users‟ study to investigate, elicit and prioritize the students‟ data-related explicit knowledge preferences of HEI domain policy. The corresponding students‟ data dimensions are then categorised, 2) exploratory study through content analysis of InfoVis design literatures, and subsequent mapping with findings from the users‟ study, to propose the appropriate visualization, interaction and distortion techniques for delivering the domain‟s explicit knowledge preferences, 3) conceptual development of the design framework which integrates the techniques‟ model with its design process–as identified from adaptation of software engineering and InfoVis design models, 4) evaluation of the proposed framework through expert review, prototyping, heuristics evaluation, and users‟ experience evaluation. For an InfoVis that will appropriately present and represent the domain explicit knowledge preferences, support the students‟ data multidimensionality and the decision making processes, the study found that: 1) mouse-on, mouse-on-click, mouse on-drag, drop down menu, push button, check boxes, and dynamics cursor hinting are the appropriate interaction techniques, 2) zooming, overview with details, scrolling, and exploration are the appropriate distortion techniques, and 3) line chart, scatter plot, map view, bar chart and pie chart are the appropriate visualization techniques. The theoretical support to the proposed framework suggests that dictates of preattentive processing theory, cognitive-fit theory, and normative and descriptive theories must be followed for InfoVis to aid perception, cognition and decision making respectively. This study contributes to the area of InfoVis, data-driven decision making process, and HEI students‟ data usage process