2009 ◽  
Vol 52 (4) ◽  
pp. 538-546 ◽  
Author(s):  
Ruimin Shen ◽  
Minjuan Wang ◽  
Wanping Gao ◽  
Daniel Novak ◽  
Lin Tang

Author(s):  
Irina Branovic ◽  
Ranko Popovic ◽  
Nenad Jovanovic ◽  
Roberto Giorgi ◽  
Bosko Nikolic ◽  
...  

Author(s):  
Wilfred Wing Fat Lau ◽  
Allan Hoi Kau Yuen

<span>The gender digital divide has been widely discussed and researched over the years. Previous studies have focused on a number of factors such as computer attitude, computer anxiety, computer self-efficacy, and computer experience. This study empirically tested the sensitivity of a learning style instrument, the </span><em>Gregorc Style Delineator</em><span> (GSD), to gender in a sample of students who studied computer programming in Hong Kong secondary schools. Results indicated that females had higher preference for concrete sequential (CS) and abstract random (AR) compared with males. Males had higher preference for concrete random (CR) than females. From these results, we proposed learning style-based pedagogical practices to teach computer programming. In order to address the needs of female students, we further proposed that learning style-based pedagogical practices need to move from a gender neutral to gender sensitive approach. This proposal helps to improve student learning through individualisation in pedagogy in terms of gender and learning styles and contributes to a gender and style sensitive computer science classroom. Eventually, through various remedial interventions, we anticipate more female participation in computer science field and hence the gender issue is addressed.</span>


2019 ◽  
Vol 22 (4) ◽  
pp. 545-567 ◽  
Author(s):  
Sepehr Vakil ◽  
Maxine McKinney de Royston

Author(s):  
Forrest Stonedahl ◽  
Michelle Wilkerson-Jerde ◽  
Uri Wilensky

The authors present a preliminary version of the MAgICS (Multi-Agent Introduction to Computer Science) framework, which is a new approach for revitalizing introductory undergraduate or high school computer science curricula through the deep integration of agent-based modeling (ABM) and multi-agent systems (MAS) perspectives. The authors discuss the merits of using multi-agent systems as a lens for conceptual understanding across disciplines, compare multi-agent approaches to traditional serial ones, and explore how this approach can bring together disparate topics in computer science through the common focus on emergent systems to promote a broader view of the field as a whole. To exemplify this approach, they have developed a suite of curricular models for topics spanning from searching and sorting to machine learning and networks and security. By introducing these topics with a focus on parallel, distributed, and stochastic methods, they can make traditionally upper-level topics both motivating and accessible to introductory-level students. The authors review findings from a short implementation of several elements of MAgICS in an introductory computer science classroom with regard to student motivation and evidence of learning of distributed design strategies.


2007 ◽  
Vol 39 (1) ◽  
pp. 514-518 ◽  
Author(s):  
Josh Tenenberg ◽  
Sally Fincher

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