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In this paper, the second draft of a new model (Bounded Innovation Management Model, BIMM) based in part on systems thinking principles, is presented to contribute to the research being conducted in mapping patterns of innovation. This is an exploratory study in the application of BIMM to a small innovative software development company in New Zealand. The eight constructs of BIMM (structure, communication, control, emergence, role, incentive, outcome and whole system) are applied to individual employees' responses in order to gain insights into innovative pattern mapping within the company. From analyzing the data from these individual responses within this company it has been discovered that: (i) evolutionary innovation patterns oscillate about and are contained by, the bounds that are in place through management practices; (ii) revolutionary patterns of innovation tend to operate outside such bounds and oscillate in the surrounding space; (iii) creative patterns tend to be stifled if completely contained within management bounds; and (iv) employees' perceived mappings of patterns of innovation may vary from the actual patterns within an organization. [ABSTRACT FROM AUTHOR]

In this paper, the second draft of a new model (Bounded Innovation Management Model, BIMM) based in part on systems thinking principles, is presented to contribute to the research being conducted in mapping patterns of innovation. This is an exploratory study in the application of BIMM to a small innovative software development company in New Zealand. The eight constructs of BIMM (structure, communication, control, emergence, role, incentive, outcome and whole system) are applied to individual employees' responses in order to gain insights into innovative pattern mapping within the company. From analyzing the data from these individual responses within this company it has been discovered that: (i) evolutionary innovation patterns oscillate about and are contained by, the bounds that are in place through management practices; (ii) revolutionary patterns of innovation tend to operate outside such bounds and oscillate in the surrounding space; (iii) creative patterns tend to be stifled if completely contained within management bounds; and (iv) employees' perceived mappings of patterns of innovation may vary from the actual patterns within an organization. [ABSTRACT FROM AUTHOR]

Aim/Purpose We aimed to investigate the circumstances under which Kahoot! (a Game-based Student Response System (GSRS)) increases junior and senior Information Science university students' learning and knowledge retention beyond that of traditional teaching methods. We also explored whether the positive learning impacts of Kahoot! vary as a function of student subject knowledge (i.e., junior vs senior students). Background The effectiveness of game-based student response systems (GSRSs) as learning tools in the classroom remains unclear, given inconsistent findings across educational research. Kahoot! enhances secondary and tertiary students' attention and motivation during class, but its effectiveness on learning and retention of course knowledge may vary depending on situational and individual factors. In New Zealand universities, students spend three years studying towards a Bachelor's degree, majoring in subject(s) of their choice. By the end of their third year of study, students are eligible to graduate with a sound knowledge of their chosen major. Thus, first-year students (referred to as "junior students") and third-year students ("senior students") may differ in terms of their learning styles and their ability and willingness to integrate Kahoot! use into their course work and revision. It is hypothesised that differences in subject knowledge between junior versus senior students will influence the perceived effectiveness of Kahoot!. Methodology Thirteen first-year (junior) and fourteen third-year (senior) Information Science students (total n = 27), who used Kahoot! in seven lectures (for 30 minutes per lecture) were interviewed about their perception of Kahoot!'s effectiveness. We conducted a mixed-methods case study of students' interview transcripts, demographic records and student scores, where thematic (content) analysis was used to analyse interview responses. Then, we quantified themes for a one-way ANCOVA, with student subject knowledge predicting Kahoot!'s effectiveness, when controlling for students' duration of tertiary study and study habits (i.e., hours dedicated to course work per week) as potential confounders. Contribution This study addresses the conflict in existing literature around whether GSRSs improve student learning beyond traditional teaching methods. To our knowledge, this is the first study that shows GSRSs (namely Kahoot!) use improves, or at least, supplements tertiary students' learning and knowledge retention of lecture content. This study also reveals how student characteristics (i.e., accumulated tertiary experience) and their subject knowledge influence the effectiveness of Kahoot! as a learning tool. Findings Kahoot!'s use increased students' learning and knowledge retention, among other positive impacts (e.g., attention and engagement). However, the perceived learning impact of Kahoot! was greater for senior students. Senior students found Kahoot! more useful for learning new knowledge and revising previously acquired knowledge. On the other hand, while junior students also experienced positive learning impacts using Kahoot!, they reported concerns regarding limited and shallow content coverage, and the time-consuming and distracting nature of the platform. Recommendations for Practitioners Educators should take care to ensure GSRSs are appropriately implemented to support rather than replace traditional teaching methods (e.g., "chalk and talk" style presentations, PowerPoint use). In addition, lecturers using GSRSs should clearly inform students about the examinable content and their expectations for performance in formal assessments. Recommendations for Researchers The positive impact of Kahoot! use on students' learning and knowledge retention may be due to stronger interactions and engagement during class. Researchers should more closely explore how student-lecturer interactions and in-depth discussions following GSRS use influence learning. Thus, there is a need to reevaluate Malone's (1980) intrinsic motivation theory in relation to the "interactive" or "enjoyability" components experienced during Kahoot! use. Impact on Society The positive impacts of Kahoot! use on student learning vary for junior and senior students. However, our findings indicate that both cohorts of students benefit from 15-minute Kahoot! sessions at the end of a lecture or course unit, allowing them to test their knowledge and revise* previously taught material. Kahoot! provides a comfortable platform that allows students to ask and answer questions without embarrassment. More experienced students can also evaluate their learning by creating their own Kahoot! quizzes and providing feedback to the lecturers. Overall, Kahoot! use could have a positive impact on teaching and learning globally. Future Research Beyond the recommendation for researchers above, future research should explore how differences in lecturers' teaching styles and students' self-regulation of learning impact Kahoot!'s effectiveness as a learning tool. [ABSTRACT FROM AUTHOR]

The under-representation and poor retention of women in computing courses at Victoria University is a concern that has continued to defy all attempts to resolve it. Despite a range of initiatives created to encourage participation and improve retention of females in the courses, the percentage of female enrollments has declined significantly in recent years, from 32% in 1994 to 18% in 2004, while attrition rates soared to 40% in 2003. A recent research study investigated these negative trends with respect to gender equity in computing courses: of interest was the possibility of gender bias in the learning environment and its impact on female attrition rates. Focus groups and surveys involving computing students of both genders were used as data collection tools in the study. The overall findings from the focus groups were rather surprising, as they yielded no strong indication of gender bias in the learning environment of the computing course; this applied to the logistical arrangements, academic staff, pedagogical methods, and course content. The thesis that the existence of gender bias in the learning environment contributes to high attrition rates of females in computing courses was not sufficiently supported. While the fact that students, both male and female, found their learning environment gender neutral was comforting, the realization that reasons other than gender bias drove females away from the computing course was not. High attrition rate of females remains the reality. Possible explanations of this phenomenon were suggested by the focus groups, and the search for confirmation of these indications and discovery of other contributing factors continued. The results of a subsequent survey confirmed several of the focus groups findings: the lack of gender balance in the course was considered immaterial, as was the gender of the lecturers and tutors; the course curriculum was deemed gender neutral; and, overall difficulty of the course and overall satisfaction with the course were rated similarly by both male and female students. Some of the survey results contradicted findings of the focus groups, notably the reported equal access to computers in laboratories and group-work unaffected by the gender of group members. Moreover, although female students did not regard the under-representation of females in the course as a problem, they singled out their fellow female students as the vital source of both academic and personal help, thereby reiterating the need for female peers in the course. The first year, particularly the first semester, of the course emerged as the 'make or break' period especially for female students. Not only was it an important period with respect to adjustment to the course but also it was a period most likely to influence most female students' decisions about quitting the course. It appears that staff encouragement mattered little in dissuading female students from quitting, but the support of fellow students was important. Transition into the course, rather than gender bias, was identified as a possible factor contributing to high attrition rates of females in computing courses. Not only did the female students take considerably longer to settle into the course - up to six months, but they also were most likely to drop out of the course after the first year of study. This is of concern for two reasons: firstly, because of the large number of students contemplating dropping out; and secondly, because the role of the academic staff in persuading those students to stay was regarded as largely insignificant by the students. This study provides some explanation of the high attrition of females in computing courses, but the challenge still remains to develop effective strategies to halt this negative trend. [ABSTRACT FROM PUBLISHER]