Using specialist software for qualitative data analysis. [Closing seminar]

This paper is divided in four parts. The first part provides some background information on the analysis of non-numerical data, specifically the content analysis of text, including approaches such as ‘grounded theory’ and ‘recursive comparative analysis’. In the second section, the use of computers for qualitative data analysis is discussed, with particular reference to its general advantages and misconceptions. The third section outlines the possibilities of some specialist software programmes for qualitative data analysis (NVivo and MAXqda). Finally, an example of the use of specialist software in a recently completed research project funded by the ESRC Teaching and Learning Research Programme is examined

Categorisation of visualisation methods to support the design of Human-Computer Interaction systems

During the design of Human-Computer Interaction (HCI) systems, the creation of visual artefacts forms an important part of design. On one hand producing a visual artefact has a number of advantages: it helps designers to externalise their thought and acts as a common language between different stakeholders. On the other hand, if an inappropriate visualisation method is employed it could hinder the design process. To support the design of HCI systems, this paper reviews the categorisation of visualisation methods used in HCI. A keyword search is conducted to identify a) current HCI design methods, b) approaches of selecting these methods. The resulting design methods are filtered to create a list of just visualisation methods. These are then categorised using the approaches identified in (b). As a result 23 HCI visualisation methods are identified and categorised in 5 selection approaches (The Recipient, Primary Purpose, Visual Archetype, Interaction Type, and The Design Process).Innovate UK, EPSRC, Airbus Group Innovation

Meaningful Categorisation of Novice Programmer Errors

The frequency of different kinds of error made by students learning to write computer programs has long been of interest to researchers and educators. In the past, various studies investigated this topic, usually by recording and analysing compiler error messages, and producing tables of relative frequencies of specific errors diagnostics produced by the compiler. In this paper, we improve on such prior studies by investigating actual logical errors in student code, as opposed to diagnostic messages produced by the compiler. The actual errors reported here are more precise, more detailed and more accurate than the diagnostic produced automatically

Information needs after stroke: What to include and how to structure it on a website. A qualitative study using focus groups and card sorting

Background: Use of the Internet to obtain health and other information is increasing. Previous studies have identified the specific information needs of people with stroke but not in relation to the Internet. People with aphasia (PwA) may face barriers in accessing the Internet: Navigating websites requires an ability to categorise information and this ability is often impaired in PwA. The website categorisation preferences of people with stroke and with aphasia have not yet been reported. Aims: This study aimed: (a) to determine what information people who have had a stroke would like to see on a website about living with stroke; (b) to determine the most effective means of structuring information on the website so that it is accessible to people with stroke; and c) to identify any differences between people with and without aphasia in terms of preferences for structuring information on the website. Methods & Procedures: Participants were recruited from a hospital's Stroke Database. Focus groups were used to elicit what information participants wanted on a website about living with stroke. The themes raised were depicted on 133 cards. To determine the most effective way of structuring information on the website, and whether there were any differences in preferences between PwA and PwoA, participants used a modified closed card-sorting technique to sort the cards under website categories. Outcomes & Results: A total of 48 people were invited, and 12 (25%) agreed to take part. We ran three focus groups: one with PwA (n = 5) and two with people without aphasia (PwoA) (n = 3, n = 4). Participants wanted more information about stroke causes and effects (particularly emotional issues), roles of local agencies, and returning to previous activities (driving, going out). All participants completed the card-sorting exercise. Few cards (6%) were categorised identically by everyone. Cards relating to local agencies and groups were not consistently categorised together. Cards relating to emotions were segregated. The categorisation preferences for PwA were more fragmented than those for PwoA: 60% of PwA agreed on the categorisation of 51% of the cards, whereas 60% of PwoA agreed on the categorisation of 76% of the cards. Conclusions: Information needs covered all stages of the stroke journey. The card sorting was accessible to everyone, and provided evidence of structuring preferences and of some of the categorisation difficulties faced by PwA. More research is needed on what an accessible website looks like for PwA

Learning Through Rich Environments

Research into games in education most frequently expresses itself in the form of noting that games interest and motivate, and that we might therefore find the learning process improved if we were to use games as a vehicle for the delivery of learning content. We do not wish to take this approach, but to analyse what it is that makes games interesting and motivating and apply this in the context of designing learning scenarios. Many papers propose taxonomies of game style and criteria for good game design, tending to list good ideas and observed issues, but meeting difficulties when trying to generalise. We review some of the more important contributions in the area, and distil these into models to help us understand what's involved by defining the concept of a “Rich Environment.” We conclude with an example of how these models may be applied to the design of a learning environment

The impact of Group Intelligence software on enquiry-based learning

Despite the increasing use of groupware technologies in education, there is little evidence of their impact, especially within an enquiry-based learning (EBL) context. In this paper, we examine the use of a commercial standard Group Intelligence software called GroupSystems®ThinkTank. To date, ThinkTank has been adopted mainly in the USA and supports teams in generating ideas, categorising, prioritising, voting and multi-criteria decision-making and automatically generates a report at the end of each session. The software was used by students carrying out an EBL project, set by employers, for a full academic year. The criteria for assessing the impact of ThinkTank on student learning were those of creativity, participation, productivity, engagement and understanding. Data was collected throughout the year using a combination of interviews and questionnaires, and written feedback from employers. The overall findings show an increase in levels of productivity and creativity, evidence of a deeper understanding of their work but some variation in attitudes towards participation in the early stages of the project

Using software to tell a trustworthy, convincing and useful story

This paper discusses the potential of specialist software to develop category construction in qualitative data analysis and considers how the uses of software may best be reported to substantiate researchers’ claims. Examples are examined from two recent projects: a consultation of pupil’s perceptions of assessment for learning strategies and an exploratory enquiry on employing music as a tool for inclusion in post-conflict Northern Ireland. From this experience, a number of suggestions on how to support the researchers’ claims are made and a model of knowledge generation is put forward. Some of the practical implications outlined are discussed within the context of social research, but it is acknowledged that the suggestions also apply to any field in which knowledge is generated from qualitative data