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Most boys and girls interact differently with educational software and have different preferences for the design of educational software. The question is whether the usage of educational software has the same consequences for both genders. This paper investigates the characteristics of drill-and-practice programmes or drills that are efficient for boys and girls. The experiment was carried out in order to find out the characteristics of drills that have statistically significant correlations with the learning outcome of boys and girls. The findings about statistically significant gender differences will be discussed. The paper concludes with some recommendations for composing drills appropriate for both genders.
As visual connectivity improves, an opportunity to enrich and rethink the place of learning design in online and distance education is presenting itself. The opportunity is derived from the increasing scope for personalised synchronous interaction which has been missing in computer mediated communications (CMC) and previous generations of distance education. This paper presents a model which distinguishes between planned learner-content interaction and learner-learner interaction and suggests that a blend of planned and non-planned learner-learner interaction is worthwhile. It concentrates on technology enhanced learning using video communications which provide opportunities for more authentic online collaborative learning, formally and informally. This conceptualisation is underpinned by beliefs which promote constructivist and transformative learning in the hope of stimulating debate as universities focus more towards quality learning. The intent is to explore the implications of learning in higher education becoming enhanced in online environments as learner-learner dialogue occurs ‘face-to-face’, thus, extending the potential of online learner-content environments.
Many institutions encourage formative computer-based assessment (CBA), yet competing priorities mean that learners are necessarily selective about what they engage in. So how can we motivate them to engage? Can we facilitate learners to take more control of shaping their learning experience? To explore this, the Learning with Interactive Assessment (LINA) project, a small-scale study, trialed a selection of online, interactive question features designed to increase motivation, particularly of work-based learners, and to enhance learners’ ability to self-regulate their own learning experience. We present initial findings on learner perceptions of: (1) a confidence indicator tool—for learners to indicate their confidence that their answer will be correct before answering a question; (2) a learning log—for learners to insert reflections or view system-recorded information about their learning pathway; and (3) question feedback—for displaying a range of author comments. Themes emerged relating to motivational, behavioural and cognitive factors, including risk taking and skills in self-assessment. A serendipitous finding highlights learners’ frequently not reading onscreen feedback and presents perceptions on when feedback becomes most useful. Motivators and barriers to engagement and self-regulation are discussed in relation to principles of best feedback practice.
In this paper, we take a designer’s look at how the activities and data of learning and assessment can be structured in immersive virtual game environments called Massively Multi-Player Online Games (MMOG). In doing so, we examine the channels of evidence throughwhich learning and assessment activities are derived in MMOGs, offering examples of how multiple evidence channels in operation through game-based activities can be utilised to construct rich data trails for assessment.
In the conventional English as a Second Language (ESL) class-based learning environment, teachers use a fixed learning sequence and content for all students without considering the diverse needs of each individual. There is a great deal of diversity within and between classes. Hence, if students’ learning outcomes are to be maximised, it is important to know how to provide learning content using students’ preferences, learning characteristics and knowledge background as a basis. A five-step algorithm was proposed that was based on the four factors (gender, learning motivation, cognitive style and learning style) as the different learner characteristics. The percentage increase between the pretest and posttest scoreswas used to determine optimal adaptive learning sequences to accommodate a variety of individual differences. The algorithm included the following five steps—to obtain the learning performance, to distinguish the learning performance of the lowest and highest groups, to use the different learning sequences as a basis for categorisation, to test the four factors between the lowest and highest performance, and to reduce the number of handouts. Finally, an empirical study for validating the adaptive learning sequence was conducted. By analysing the students’ characteristics and the optimal learning sequences, an attempt was made to develop an adaptive learning sequence system to facilitate students’ learning and to maximise their learning outcome, thus addressing the problem of fixed learning sequences in conventional ESL instruction.
This study investigates the navigational patterns and learning achievement of university students with different cognitive styles, on hypermedia learning environments using paging or scrolling. The global–local subscales of Sternberg’s Thinking Styles Inventory, two hypermedia, one using paging, the other using scrolling, a multiple choice achievement test, and a questionnaire to collect the students’ satisfaction on paging/scrolling were used as data collection tools. This study finds that the cognitive style and paging/scrolling, together or separately, neither affected the learning nor the satisfaction of learners. Students with different cognitive styles using paging or scrolling did all learn well, with no statistically significant difference. Also the navigation patterns did not seem to depend on cognitive style; that is, the frequencies of using the navigation tools were not significantly different.
Using text mining to uncover students’
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