Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462324
L. Morell, Martina Y. Trucco, C. Bash, C. Patel
Information technology (IT) forms a crucial foundation for designing, building and managing future sustainable cities. This paper proposes a model to innovate the engineering and computing curriculum to include sustainability and IT topics in order to develop the skills and competencies that future professionals will need to design, build and manage future cities. Rather than developing a new program, we propose a curriculum model - called SustainIT -adapted from the successful 2006 US NAE Gordon Prize engineering curriculum innovation, The Learning Factory - as a possible roadmap to reform and complement existing Bachelors of Science (BS) degrees in engineering. By providing a series of guided electives, any engineering program may offer engineering, and/or computer science students the opportunity to learn about and become specialized in IT for Sustainability. Multidisciplinary topics include traditional ecological engineering; life-cycle design; design and application of resource microgrids; pervasive sensing and data aggregation; knowledge discovery, data mining and visualization; and, policy based control and operation for resource provisioning.
{"title":"An engineering curriculum track for IT for sustainability","authors":"L. Morell, Martina Y. Trucco, C. Bash, C. Patel","doi":"10.1109/FIE.2012.6462324","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462324","url":null,"abstract":"Information technology (IT) forms a crucial foundation for designing, building and managing future sustainable cities. This paper proposes a model to innovate the engineering and computing curriculum to include sustainability and IT topics in order to develop the skills and competencies that future professionals will need to design, build and manage future cities. Rather than developing a new program, we propose a curriculum model - called SustainIT -adapted from the successful 2006 US NAE Gordon Prize engineering curriculum innovation, The Learning Factory - as a possible roadmap to reform and complement existing Bachelors of Science (BS) degrees in engineering. By providing a series of guided electives, any engineering program may offer engineering, and/or computer science students the opportunity to learn about and become specialized in IT for Sustainability. Multidisciplinary topics include traditional ecological engineering; life-cycle design; design and application of resource microgrids; pervasive sensing and data aggregation; knowledge discovery, data mining and visualization; and, policy based control and operation for resource provisioning.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121055863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462527
Annette Berndt
This paper focuses on the knowledge construction process in a technology and society course in which engineering students propose solutions to authentic socio-technical problems in India. Student definition and use of non-academic information is examined with the recommendation that documentation practices be further developed to accurately reflect community contribution. Implications for the global engineering workplace are also addressed.
{"title":"Work in progress: What do engineering students do with non-academic information as they address authentic socio-technical problems?","authors":"Annette Berndt","doi":"10.1109/FIE.2012.6462527","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462527","url":null,"abstract":"This paper focuses on the knowledge construction process in a technology and society course in which engineering students propose solutions to authentic socio-technical problems in India. Student definition and use of non-academic information is examined with the recommendation that documentation practices be further developed to accurately reflect community contribution. Implications for the global engineering workplace are also addressed.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123815465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462246
Daniel Gallego, E. Barra, S. Aguirre, G. Huecas
A proactive recommender system pushes recommendations to the user when the current situation seems appropriate, without explicit user request. This is suitable in e-Learning scenarios in which a great amount of learning objects are available but it is difficult to find them according to the user's needs. In this paper, we present a model for generating proactive context-aware recommendations in the Virtual Science Hub (ViSH), a educational platform related to the GLOBAL excursion European project. The model relies on domain-dependent context modeling in several categories to generate personalized recommendations to teachers and scientists that will produce the learning resources the students will consume. The recommendation process is divided into three phases. First, the generation of the social context information related to the users in the platform. Then, the current situation considering the social, location and user context is analyzed. Finally, the suitability of particular learning objects to be recommended is examined. Therefore, details about the recommendation model proposed and advantages related to applying the model in ViSH can be found in the paper, in addition to some conclusion remarks and outlook on future work.
{"title":"A model for generating proactive context-aware recommendations in e-Learning systems","authors":"Daniel Gallego, E. Barra, S. Aguirre, G. Huecas","doi":"10.1109/FIE.2012.6462246","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462246","url":null,"abstract":"A proactive recommender system pushes recommendations to the user when the current situation seems appropriate, without explicit user request. This is suitable in e-Learning scenarios in which a great amount of learning objects are available but it is difficult to find them according to the user's needs. In this paper, we present a model for generating proactive context-aware recommendations in the Virtual Science Hub (ViSH), a educational platform related to the GLOBAL excursion European project. The model relies on domain-dependent context modeling in several categories to generate personalized recommendations to teachers and scientists that will produce the learning resources the students will consume. The recommendation process is divided into three phases. First, the generation of the social context information related to the users in the platform. Then, the current situation considering the social, location and user context is analyzed. Finally, the suitability of particular learning objects to be recommended is examined. Therefore, details about the recommendation model proposed and advantages related to applying the model in ViSH can be found in the paper, in addition to some conclusion remarks and outlook on future work.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125134870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462444
Minzhe Guo, P. Bhattacharya, Ming Yang, K. Qian, Li Yang
To address the need for innovative mobile security learning materials and for promoting mobile security education, this paper presents our work-in-progress effort on developing a real-world relevant security labware to provide students with mobile threat analysis and protection experience. A preliminary evaluation has been conducted on the pilot labs and positive feedback has been received.
{"title":"Work in progress: Real world relevant security labware for mobile threat analysis and protection experience","authors":"Minzhe Guo, P. Bhattacharya, Ming Yang, K. Qian, Li Yang","doi":"10.1109/FIE.2012.6462444","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462444","url":null,"abstract":"To address the need for innovative mobile security learning materials and for promoting mobile security education, this paper presents our work-in-progress effort on developing a real-world relevant security labware to provide students with mobile threat analysis and protection experience. A preliminary evaluation has been conducted on the pilot labs and positive feedback has been received.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122839072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462430
Mikko Apiola, M. Tedre, M. Lattu, Tomi A. Pasanen
This paper focuses on understanding and developing learning environments for computer science education. We present two models that we have successfully used in European and African contexts. The first model, Computer Science Learning Environments (CSLE), presents seven dimensions of computer science courses, which should be considered in learning environment design for computer science. The second model, Investigative Learning Environment (ILE), presents an action plan model, inspired by action research, for combining educational research and computer science teaching. In the empirical section we outline two case studies where these models were used to design and implement computer science learning environments in two different learning contexts. In the first case in University of Helsinki, Finland, we developed and studied a method of learning-by-inventing in a robotics programming course. That course was designed around problem discovery and inventing, and it employed LEGO® Mindstorms robots. In the second case in Tumaini University, Tanzania, we designed an environment for studying and improving introductory programming courses. Both models showed to be useful for designing, implementing, developing, and analyzing the courses in both learning contexts.
{"title":"Towards a framework for designing and analyzing CS learning environments","authors":"Mikko Apiola, M. Tedre, M. Lattu, Tomi A. Pasanen","doi":"10.1109/FIE.2012.6462430","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462430","url":null,"abstract":"This paper focuses on understanding and developing learning environments for computer science education. We present two models that we have successfully used in European and African contexts. The first model, Computer Science Learning Environments (CSLE), presents seven dimensions of computer science courses, which should be considered in learning environment design for computer science. The second model, Investigative Learning Environment (ILE), presents an action plan model, inspired by action research, for combining educational research and computer science teaching. In the empirical section we outline two case studies where these models were used to design and implement computer science learning environments in two different learning contexts. In the first case in University of Helsinki, Finland, we developed and studied a method of learning-by-inventing in a robotics programming course. That course was designed around problem discovery and inventing, and it employed LEGO® Mindstorms robots. In the second case in Tumaini University, Tanzania, we designed an environment for studying and improving introductory programming courses. Both models showed to be useful for designing, implementing, developing, and analyzing the courses in both learning contexts.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127646509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462477
Thomas J. Cortina, W. Dann, C. Frieze, Cara Ciminillo, Cynthia A. Tananis, Keith Trahan
In the Northern Appalachian region around Pittsburgh, PA, many high schools do not have computer science courses, so students are not introduced to this critical subject that is needed for most technical career paths. Our unique strategy is to invite current high school science, technology, engineering and mathematics (STEM) teachers, in Pennsylvania, West Virginia, Ohio and Maryland, to participate in 3 summer workshops showing how to incorporate computing concepts into existing STEM courses. By working with teachers on how to assimilate programming and computational thinking into their classrooms we will effectively reach a large population of students in areas where computer science classes are not available. In this paper, we outline the current state of the project and some of the data we have collected. Future goals for this project include performing a rigorous evaluation of teacher impact and developing the workshop materials for wider dissemination.
{"title":"Work in progress: ACTIVATE: Advancing computing and technology interest and innovation through teacher education","authors":"Thomas J. Cortina, W. Dann, C. Frieze, Cara Ciminillo, Cynthia A. Tananis, Keith Trahan","doi":"10.1109/FIE.2012.6462477","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462477","url":null,"abstract":"In the Northern Appalachian region around Pittsburgh, PA, many high schools do not have computer science courses, so students are not introduced to this critical subject that is needed for most technical career paths. Our unique strategy is to invite current high school science, technology, engineering and mathematics (STEM) teachers, in Pennsylvania, West Virginia, Ohio and Maryland, to participate in 3 summer workshops showing how to incorporate computing concepts into existing STEM courses. By working with teachers on how to assimilate programming and computational thinking into their classrooms we will effectively reach a large population of students in areas where computer science classes are not available. In this paper, we outline the current state of the project and some of the data we have collected. Future goals for this project include performing a rigorous evaluation of teacher impact and developing the workshop materials for wider dissemination.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132581323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462206
W. Schilling
This paper discusses a novel active learning exercise which teaches students how to perform and assess the effectiveness of formal software inspections. In this exercise, students are responsible for selecting an artifact from their senior capstone design projects. The students then use fault injection to strategically place faults within the artifact that should be caught by the inspection exercise. Based on the needs of the team, students prepare an inspection packet consisting of a set of inspection instructions, applicable checklists, and the inspection artifact. Students then “hire” a set of inspectors based on classmates' backgrounds and experiences. The team leader then holds two inspection meetings and reports the results. The results are then used to assess the effectiveness of the inspection. Overall, in analyzing 5 years worth of data from this exercise, it is found that students are capable of selecting appropriate materials for inspection and performing appropriate software inspections. The yield of students is lower than an experienced professional might have and the inspection rates tend to be slightly higher than desired for their experience. However, the yield is related to individual preparation time. Students overall find this to be a highly educational experience and highly recommend it be continued for future classes.
{"title":"Teaching software inspection effectiveness: An active learning exercise","authors":"W. Schilling","doi":"10.1109/FIE.2012.6462206","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462206","url":null,"abstract":"This paper discusses a novel active learning exercise which teaches students how to perform and assess the effectiveness of formal software inspections. In this exercise, students are responsible for selecting an artifact from their senior capstone design projects. The students then use fault injection to strategically place faults within the artifact that should be caught by the inspection exercise. Based on the needs of the team, students prepare an inspection packet consisting of a set of inspection instructions, applicable checklists, and the inspection artifact. Students then “hire” a set of inspectors based on classmates' backgrounds and experiences. The team leader then holds two inspection meetings and reports the results. The results are then used to assess the effectiveness of the inspection. Overall, in analyzing 5 years worth of data from this exercise, it is found that students are capable of selecting appropriate materials for inspection and performing appropriate software inspections. The yield of students is lower than an experienced professional might have and the inspection rates tend to be slightly higher than desired for their experience. However, the yield is related to individual preparation time. Students overall find this to be a highly educational experience and highly recommend it be continued for future classes.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115217649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462205
D. Petkovic, K. Okada, Marc Sosnick-Pérez, Aishwarya Iyer, S. Zhu, R. Todtenhoefer, Shihong Huang
One of the challenges in effective software engineering (SE) education is the lack of objective assessment methods of how well student teams learn the critically needed teamwork practices, defined as the ability: (i) to learn and effectively apply SE processes in a teamwork setting, and (ii) to work as a team to develop satisfactory software (SW) products. In addition, there are no effective methods for predicting learning effectiveness in order to enable early intervention in the classroom. Most of the current approaches to assess achievement of SE teamwork skills rely solely on qualitative and subjective data taken as surveys at the end of the class and analyzed only with very rudimentary data analysis. In this paper we present a novel approach to address the assessment and prediction of student learning of teamwork effectiveness in software engineering education based on: a) extracting only objective and quantitative student team activity data during their team class project; b) pairing these data with related independent observations and grading of student team effectiveness in SE process and SE product components in order to create “training database” and c) applying a machine learning (ML) approach, namely random forest classification (RF), to the above training database in order to create ML models, ranked factors and rules that can both explain (e.g. assess) as well as provide prediction of the student teamwork effectiveness. These student team activity data are being collected in joint and already established (since 2006) SE classes at San Francisco State University (SFSU), Florida Atlantic University (FAU) and Fulda University, Germany (Fulda), from approximately 80 students each year, working in about 15 teams, both local and global (with students from multiple schools).
{"title":"Work in progress: A machine learning approach for assessment and prediction of teamwork effectiveness in software engineering education","authors":"D. Petkovic, K. Okada, Marc Sosnick-Pérez, Aishwarya Iyer, S. Zhu, R. Todtenhoefer, Shihong Huang","doi":"10.1109/FIE.2012.6462205","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462205","url":null,"abstract":"One of the challenges in effective software engineering (SE) education is the lack of objective assessment methods of how well student teams learn the critically needed teamwork practices, defined as the ability: (i) to learn and effectively apply SE processes in a teamwork setting, and (ii) to work as a team to develop satisfactory software (SW) products. In addition, there are no effective methods for predicting learning effectiveness in order to enable early intervention in the classroom. Most of the current approaches to assess achievement of SE teamwork skills rely solely on qualitative and subjective data taken as surveys at the end of the class and analyzed only with very rudimentary data analysis. In this paper we present a novel approach to address the assessment and prediction of student learning of teamwork effectiveness in software engineering education based on: a) extracting only objective and quantitative student team activity data during their team class project; b) pairing these data with related independent observations and grading of student team effectiveness in SE process and SE product components in order to create “training database” and c) applying a machine learning (ML) approach, namely random forest classification (RF), to the above training database in order to create ML models, ranked factors and rules that can both explain (e.g. assess) as well as provide prediction of the student teamwork effectiveness. These student team activity data are being collected in joint and already established (since 2006) SE classes at San Francisco State University (SFSU), Florida Atlantic University (FAU) and Fulda University, Germany (Fulda), from approximately 80 students each year, working in about 15 teams, both local and global (with students from multiple schools).","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115696224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462262
S. Condoor, Greg S. Keogh
While the value of the entrepreneurial mindset in engineering is now well recognized, faculty members are still struggling to find curricular and extracurricular activities to instill this mindset. This paper presents weekly innovation challenges as a relatively easy to implement set of activities that can be incorporated into: i) Existing courses as impromptu competitions and icebreakers that require no major curricular overhaul ii) Extracurricular activities to effectively engage students and faculty, and iii) Outreach activities to promote STEM and entrepreneurship through summer camps, engineers week competitions, K-12 outreach, and open-house events. The goal of the weekly innovation challenges is to instill the entrepreneurial mindset and foster interdisciplinary team to address a need under tight time constraints. In the long-term, the challenges have the potential to change the eco-system of the entire school. This paper provides insights into the organization of such challenges and logistics in conducting them.
{"title":"Work in progress: Weekly innovation challenge: Changing the mindset one step at a time every week","authors":"S. Condoor, Greg S. Keogh","doi":"10.1109/FIE.2012.6462262","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462262","url":null,"abstract":"While the value of the entrepreneurial mindset in engineering is now well recognized, faculty members are still struggling to find curricular and extracurricular activities to instill this mindset. This paper presents weekly innovation challenges as a relatively easy to implement set of activities that can be incorporated into: i) Existing courses as impromptu competitions and icebreakers that require no major curricular overhaul ii) Extracurricular activities to effectively engage students and faculty, and iii) Outreach activities to promote STEM and entrepreneurship through summer camps, engineers week competitions, K-12 outreach, and open-house events. The goal of the weekly innovation challenges is to instill the entrepreneurial mindset and foster interdisciplinary team to address a need under tight time constraints. In the long-term, the challenges have the potential to change the eco-system of the entire school. This paper provides insights into the organization of such challenges and logistics in conducting them.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114497964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-03DOI: 10.1109/FIE.2012.6462263
H. Freitas
Parallel programming is an important issue for current multi-core processors and necessary for new generations of many-core architectures. This includes processors, computers, and clusters. However, the introduction of parallel programming in undergraduate courses demands new efforts to prepare students for this new reality. This paper describes an experiment on a traditional Computer Science course during a two-year period. The main focus is the question of when to introduce parallel programming models in order to improve the quality of learning. The goal is to propose a method of introducing parallel programming based on OpenMP (a shared-variable model) and MPI (a message-passing model). Results show that when the OpenMP model is introduced before the MPI model the best results are achieved. The main contribution of this paper is the proposed method that correlates several concepts such as concurrency, parallelism, speedup, and scalability to improve student motivation and learning.
{"title":"Introducing parallel programming to traditional undergraduate courses","authors":"H. Freitas","doi":"10.1109/FIE.2012.6462263","DOIUrl":"https://doi.org/10.1109/FIE.2012.6462263","url":null,"abstract":"Parallel programming is an important issue for current multi-core processors and necessary for new generations of many-core architectures. This includes processors, computers, and clusters. However, the introduction of parallel programming in undergraduate courses demands new efforts to prepare students for this new reality. This paper describes an experiment on a traditional Computer Science course during a two-year period. The main focus is the question of when to introduce parallel programming models in order to improve the quality of learning. The goal is to propose a method of introducing parallel programming based on OpenMP (a shared-variable model) and MPI (a message-passing model). Results show that when the OpenMP model is introduced before the MPI model the best results are achieved. The main contribution of this paper is the proposed method that correlates several concepts such as concurrency, parallelism, speedup, and scalability to improve student motivation and learning.","PeriodicalId":120268,"journal":{"name":"2012 Frontiers in Education Conference Proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117160822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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