Research has shown that social influence can be used to effect behavior change. However, research on the role culture plays in the effect of age and gender on social influence in persuasive technology is scarce. To address this, we investigate the effect of age and gender on the susceptibility of individuals to Competition, Reward, Social Comparison and Social Learning in individualist and collectivist cultures, using a sample of 360 participants from North America, Africa and Asia. Our results reveal that there are more significant differences between males and females and between younger and older people in collectivist cultures than individualist cultures. In individualist culture, we found that males and females differ with respect to Competition only, with males being more susceptible. However, in collectivist culture, we found males differ from females with respect to Reward and Competition, with males being more susceptible, while younger people differ from older people with respect to Competition, Social Comparison and Social Learning, with younger people be more susceptible. Our findings provide designers of gamified persuasive applications with empirical insights for tailoring to the different cultures based on age and gender
{"title":"The Influence of Culture in the Effect of Age and Gender on Social Influence in Persuasive Technology","authors":"Kiemute Oyibo, Rita Orji, Julita Vassileva","doi":"10.1145/3099023.3099071","DOIUrl":"https://doi.org/10.1145/3099023.3099071","url":null,"abstract":"Research has shown that social influence can be used to effect behavior change. However, research on the role culture plays in the effect of age and gender on social influence in persuasive technology is scarce. To address this, we investigate the effect of age and gender on the susceptibility of individuals to Competition, Reward, Social Comparison and Social Learning in individualist and collectivist cultures, using a sample of 360 participants from North America, Africa and Asia. Our results reveal that there are more significant differences between males and females and between younger and older people in collectivist cultures than individualist cultures. In individualist culture, we found that males and females differ with respect to Competition only, with males being more susceptible. However, in collectivist culture, we found males differ from females with respect to Reward and Competition, with males being more susceptible, while younger people differ from older people with respect to Competition, Social Comparison and Social Learning, with younger people be more susceptible. Our findings provide designers of gamified persuasive applications with empirical insights for tailoring to the different cultures based on age and gender","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"130 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113960486","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}
Since 2007, the PATCH workshop series have been a gathering place for researchers and professionals from various countries and institutions to discuss the topics of digital access to Cultural Heritage and specifically the personalization aspects of this process. Due to this rich history, the reach of the PATCH workshop in various research communities is extensive. PATCH 2017 is another link in the long chain of PATCH events and we hope that it will point out future research challenges and directions and its success will pave the way to future events. Following the successful series of PATCH workshops, PATCH 2017 is organized as the meeting point between state of the art cultural heritage research and personalization -- using any kind of technology, while focusing on ubiquitous and adaptive scenarios, to enhance the personal experience in cultural heritage sites. The workshop is aimed at bringing together researchers and practitioners who are working on various aspects of cultural heritage and are interested in exploring the potential of state of the art of personalized approaches that may enhance the CH visit experience. In this edition we received 7 submissions, 2 full papers (28%), 3 short papers (42%), 1 demo paper (14%), and 1 position paper (14%). To select the workshop papers a peer-review process was carried out. At least three members of the Program Committee (which is listed below) were assigned to each paper. As result, we have accepted all the papers, and downgraded 1 short paper to position paper. The 2017 workshop includes contributions covering diverse research aspects, such as: advanced brain informatics and IoT approaches to understand museum visitors' behavior or to personalize their visits; novel models for information retrieval, information visualization and automated personalized content generation, social recommendation of CH information based on Linked Open Data; and a study of the interplay among human cognitive processing differences and cultural heritage activities towards gaming experience and performance. We believe that this is a nice spectrum of topics and we wish you to enjoy reading the workshop proceedings. The contributions collected in this workshop reflect these topics.
{"title":"UMAP 2017 PATCH 2017: Personalized Access to Cultural Heritage Organizers' Welcome","authors":"L. Ardissono, Cristina Gena, T. Kuflik","doi":"10.1145/3099023.3099085","DOIUrl":"https://doi.org/10.1145/3099023.3099085","url":null,"abstract":"Since 2007, the PATCH workshop series have been a gathering place for researchers and professionals from various countries and institutions to discuss the topics of digital access to Cultural Heritage and specifically the personalization aspects of this process. Due to this rich history, the reach of the PATCH workshop in various research communities is extensive. PATCH 2017 is another link in the long chain of PATCH events and we hope that it will point out future research challenges and directions and its success will pave the way to future events. Following the successful series of PATCH workshops, PATCH 2017 is organized as the meeting point between state of the art cultural heritage research and personalization -- using any kind of technology, while focusing on ubiquitous and adaptive scenarios, to enhance the personal experience in cultural heritage sites. The workshop is aimed at bringing together researchers and practitioners who are working on various aspects of cultural heritage and are interested in exploring the potential of state of the art of personalized approaches that may enhance the CH visit experience. In this edition we received 7 submissions, 2 full papers (28%), 3 short papers (42%), 1 demo paper (14%), and 1 position paper (14%). To select the workshop papers a peer-review process was carried out. At least three members of the Program Committee (which is listed below) were assigned to each paper. As result, we have accepted all the papers, and downgraded 1 short paper to position paper. The 2017 workshop includes contributions covering diverse research aspects, such as: advanced brain informatics and IoT approaches to understand museum visitors' behavior or to personalize their visits; novel models for information retrieval, information visualization and automated personalized content generation, social recommendation of CH information based on Linked Open Data; and a study of the interplay among human cognitive processing differences and cultural heritage activities towards gaming experience and performance. We believe that this is a nice spectrum of topics and we wish you to enjoy reading the workshop proceedings. The contributions collected in this workshop reflect these topics.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129431903","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}
Augusto Dias Pereira dos Santos, K. Yacef, Roberto Martínez Maldonado
In partner dance classes, teachers typically manage several students at the same time. For that reason, the amount of feedback provided in class is quite limited and students do not have many resources to get other feedback. In this demo paper, we present Forró Trainer, a tool that allows students to practice dance exercises by themselves, receiving automatically generated feedback about their performance. The system runs on a smartphone app and focuses on a fundamental aspect of dancing: learning to follow the rhythm of the music. The app detects the student's movements, using the mobile's accelerometer, extracts aspects of the rhythm and provides feedback. We present a description of the tool, the mistakes it detects, the automated feedback and the benefits that it may provide for dance students.
{"title":"Forró Trainer: Automated Feedback for Partner Dance Learning","authors":"Augusto Dias Pereira dos Santos, K. Yacef, Roberto Martínez Maldonado","doi":"10.1145/3099023.3099032","DOIUrl":"https://doi.org/10.1145/3099023.3099032","url":null,"abstract":"In partner dance classes, teachers typically manage several students at the same time. For that reason, the amount of feedback provided in class is quite limited and students do not have many resources to get other feedback. In this demo paper, we present Forró Trainer, a tool that allows students to practice dance exercises by themselves, receiving automatically generated feedback about their performance. The system runs on a smartphone app and focuses on a fundamental aspect of dancing: learning to follow the rhythm of the music. The app detects the student's movements, using the mobile's accelerometer, extracts aspects of the rhythm and provides feedback. We present a description of the tool, the mistakes it detects, the automated feedback and the benefits that it may provide for dance students.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126844128","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}
In the past decades, the process of urbanization has shaped general socio-economic aspects of cities with different population sizes. Among them, food consumption is a good indicator to reflect the quality of life. In this paper, we study the impact of city size on food preferences, as shown by users of a large German food sharing community. We quantitatively and qualitatively analyze differences in dietary choices made by users who indicate to live in cities of different sizes, from metropolises and big cities to medium and small towns. Further, we demonstrate that the city size of the creators of online recipes can be predicted with a good accuracy of 86%, using predictors based on recipe authors' profiles, recipe popularity, season, and recipe complexity and contents. The findings indicate that city size is a useful feature to take into account in various other domains.
{"title":"The Influence of City Size on Dietary Choices","authors":"Hao Cheng, Markus Rokicki, E. Herder","doi":"10.1145/3099023.3099058","DOIUrl":"https://doi.org/10.1145/3099023.3099058","url":null,"abstract":"In the past decades, the process of urbanization has shaped general socio-economic aspects of cities with different population sizes. Among them, food consumption is a good indicator to reflect the quality of life. In this paper, we study the impact of city size on food preferences, as shown by users of a large German food sharing community. We quantitatively and qualitatively analyze differences in dietary choices made by users who indicate to live in cities of different sizes, from metropolises and big cities to medium and small towns. Further, we demonstrate that the city size of the creators of online recipes can be predicted with a good accuracy of 86%, using predictors based on recipe authors' profiles, recipe popularity, season, and recipe complexity and contents. The findings indicate that city size is a useful feature to take into account in various other domains.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130498644","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}
Vasileios Triglianos, M. Lábaj, Róbert Móro, Jakub Simko, M. Hucko, Jozef Tvarozek, C. Pautasso, M. Bieliková
Modern constructivist approaches to education dictate active experimentation with the study material and have been linked with improved learning outcomes in STEM fields. During classroom time we believe it is important for students to experiment with the lecture material since active recall helps them to start the memory encoding process as well as to catch misconceptions early and to prevent them from taking root. In this paper, we report on our experiences using ASQ, a Web-based interactive presentation tool in a functional and logic programming course taught at the Faculty of Informatics and Information Technologies at the Slovak University of Technology in Bratislava. ASQ allowed us to collect immediate feedback from students and retain their attention by asking complex types of questions and aggregating student answers in real time. From our experience we identified several requirements and guidelines for successfully adopting ASQ. One of the most critical concerns was how to estimate the time when to stop collecting the students' answers and proceed to their evaluation and discussion with the class. We also report the students' feedback on the ASQ system that we collected in the form of the standard SUS questionnaire.
{"title":"Experiences Using an Interactive Presentation Platform in a Functional and Logic Programming Course","authors":"Vasileios Triglianos, M. Lábaj, Róbert Móro, Jakub Simko, M. Hucko, Jozef Tvarozek, C. Pautasso, M. Bieliková","doi":"10.1145/3099023.3099082","DOIUrl":"https://doi.org/10.1145/3099023.3099082","url":null,"abstract":"Modern constructivist approaches to education dictate active experimentation with the study material and have been linked with improved learning outcomes in STEM fields. During classroom time we believe it is important for students to experiment with the lecture material since active recall helps them to start the memory encoding process as well as to catch misconceptions early and to prevent them from taking root. In this paper, we report on our experiences using ASQ, a Web-based interactive presentation tool in a functional and logic programming course taught at the Faculty of Informatics and Information Technologies at the Slovak University of Technology in Bratislava. ASQ allowed us to collect immediate feedback from students and retain their attention by asking complex types of questions and aggregating student answers in real time. From our experience we identified several requirements and guidelines for successfully adopting ASQ. One of the most critical concerns was how to estimate the time when to stop collecting the students' answers and proceed to their evaluation and discussion with the class. We also report the students' feedback on the ASQ system that we collected in the form of the standard SUS questionnaire.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131180949","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}
The intent-aware diversification framework considers a set of aspects associated with items to be recommended. A baseline recommendation is greedily re-ranked using an objective that promotes diversity across the aspects. In this paper the framework is analysed and a new intent-aware objective is derived that considers the minimum variance criterion, connecting the framework directly to portfolio diversification from finance. We derive an aspect model that supports the goal of minimum variance and that is faithful to the underlying baseline algorithm. We evaluate diversification capabilities of the proposed method on the MovieLens dataset.
{"title":"Personalised Diversification Using Intent-Aware Portfolio","authors":"Jacek Wasilewski, N. Hurley","doi":"10.1145/3099023.3099067","DOIUrl":"https://doi.org/10.1145/3099023.3099067","url":null,"abstract":"The intent-aware diversification framework considers a set of aspects associated with items to be recommended. A baseline recommendation is greedily re-ranked using an objective that promotes diversity across the aspects. In this paper the framework is analysed and a new intent-aware objective is derived that considers the minimum variance criterion, connecting the framework directly to portfolio diversification from finance. We derive an aspect model that supports the goal of minimum variance and that is faithful to the underlying baseline algorithm. We evaluate diversification capabilities of the proposed method on the MovieLens dataset.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132310951","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}
Elke E. Mattheiss, Marc Busch, Rita Orji, G. F. Tondello, Andrzej Marczewski, Wolfgang Hochleitner, M. Lankes, M. Tscheligi
It is our great pleasure to welcome you to the UMAP 2017 Fifty Shades of Personalization - Workshop on Personalization in Serious and Persuasive Games and Gameful Interactions. Serious games (games for purposes other than entertainment) as well as persuasive games (games for promoting desirable behavior without coercion) are increasingly adopted by scholars and have also found their way into industry. Elements of games are also increasingly used to design gameful interactions (this is also referred to as gamification). Serious and persuasive approaches focus on imparting knowledge and raising awareness about topics or issues, and also fostering attitude or behavior change in a desirable direction, for example towards a healthier lifestyle. In an era when we are used to highly individualized, personal and ubiquitous interactions and with the possibility to collect an enormous amount of information about people's behaviors, habits and attitudes, personalization has increased much in significance since it became a topic in Human-Computer Interaction. Not only do we have advanced opportunities to personalize serious and persuasive games and gameful interactions, we have also scientific evidence that this is highly useful. Studies show that these technologies are more effective in educating users about certain topics and in supporting them in behavioral and attitudinal change, as well as in raising awareness and engaging them in specific topics, when they are personalized in contrast to employing a one-size-fits-all approach. Although personalization of serious and persuasive games and gameful interactions is a vibrant and highly promising area and has become an important researched field, many aspects of it are still underexplored. Thus, there is common understanding on the importance of personalization itself, but also an ongoing debate and a growing number of research on the approaches used for personalization: Will we use subjective or objective variables for personalization? Will we use continuous (such as traits) or categorical (such as types) dimensions? Will we personalize according to specific interactions (e.g. game dynamics) or ends of the interaction (e.g. different goals)? Will we rely on an a priori personalization or will we be able to personalize in real-time? The various shades of personalization in serious games and gameful interactions will be the central aspect of the workshop and will form the basis for participants' discussions.
{"title":"UMAP 2017 Fifty Shades of Personalization - Workshop on Personalization in Serious and Persuasive Games and Gameful Interactions: Organizers' Welcome & Organization","authors":"Elke E. Mattheiss, Marc Busch, Rita Orji, G. F. Tondello, Andrzej Marczewski, Wolfgang Hochleitner, M. Lankes, M. Tscheligi","doi":"10.1145/3099023.3099109","DOIUrl":"https://doi.org/10.1145/3099023.3099109","url":null,"abstract":"It is our great pleasure to welcome you to the UMAP 2017 Fifty Shades of Personalization - Workshop on Personalization in Serious and Persuasive Games and Gameful Interactions. Serious games (games for purposes other than entertainment) as well as persuasive games (games for promoting desirable behavior without coercion) are increasingly adopted by scholars and have also found their way into industry. Elements of games are also increasingly used to design gameful interactions (this is also referred to as gamification). Serious and persuasive approaches focus on imparting knowledge and raising awareness about topics or issues, and also fostering attitude or behavior change in a desirable direction, for example towards a healthier lifestyle. In an era when we are used to highly individualized, personal and ubiquitous interactions and with the possibility to collect an enormous amount of information about people's behaviors, habits and attitudes, personalization has increased much in significance since it became a topic in Human-Computer Interaction. Not only do we have advanced opportunities to personalize serious and persuasive games and gameful interactions, we have also scientific evidence that this is highly useful. Studies show that these technologies are more effective in educating users about certain topics and in supporting them in behavioral and attitudinal change, as well as in raising awareness and engaging them in specific topics, when they are personalized in contrast to employing a one-size-fits-all approach. Although personalization of serious and persuasive games and gameful interactions is a vibrant and highly promising area and has become an important researched field, many aspects of it are still underexplored. Thus, there is common understanding on the importance of personalization itself, but also an ongoing debate and a growing number of research on the approaches used for personalization: Will we use subjective or objective variables for personalization? Will we use continuous (such as traits) or categorical (such as types) dimensions? Will we personalize according to specific interactions (e.g. game dynamics) or ends of the interaction (e.g. different goals)? Will we rely on an a priori personalization or will we be able to personalize in real-time? The various shades of personalization in serious games and gameful interactions will be the central aspect of the workshop and will form the basis for participants' discussions.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122935853","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}
Increasing diversity in the output of a recommender system is an active research question for solving a long-tail issue. Most of the current approaches have focused on ranked list optimization to improve recommendation diversity. However, little is known about the effect that a visual interface can have on this issue. This paper shows that a multidimensional visualization promotes diversity of social exploration in the context of an academic conference. Our study shows a significant difference in the exploration pattern between ranked list and visual interfaces. The results show that a visual interface can help the user explore a a more diverse set of recommended items.
{"title":"Leveraging Interfaces to Improve Recommendation Diversity","authors":"Chun-Hua Tsai, Peter Brusilovsky","doi":"10.1145/3099023.3099073","DOIUrl":"https://doi.org/10.1145/3099023.3099073","url":null,"abstract":"Increasing diversity in the output of a recommender system is an active research question for solving a long-tail issue. Most of the current approaches have focused on ranked list optimization to improve recommendation diversity. However, little is known about the effect that a visual interface can have on this issue. This paper shows that a multidimensional visualization promotes diversity of social exploration in the context of an academic conference. Our study shows a significant difference in the exploration pattern between ranked list and visual interfaces. The results show that a visual interface can help the user explore a a more diverse set of recommended items.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126197668","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}
Hung Chau, Jordan Barria-Pineda, Peter Brusilovsky
Authoring an adaptive educational system is a complex process that involves allocating a large range of educational content within a fixed sequence of units. In this paper, we describe Content Wizard, a concept-based recommender system for recommending learning materials that meet the instructor's pedagogical goals during the creation of an online programming course. Here, the instructors are asked to provide a set of code examples that jointly reflect the learning goals that are associated with each course unit. The Wizard is built on top of our course-authoring tool, and it helps to decrease the time instructors spend on the task and to maintain the coherence of the sequential structure of the course. It also provides instructors with additional information to identify content that might be not appropriate for the unit they are creating. We conducted an off-line study with data collected from an introductory Java course previously taught at the University of Pittsburgh in order to evaluate both the practicality and effectiveness of the system. We found that the proposed recommendation's performance is relatively close to the teacher's expectation in creating a computer-based adaptive course.
{"title":"Content Wizard: Concept-Based Recommender System for Instructors of Programming Courses","authors":"Hung Chau, Jordan Barria-Pineda, Peter Brusilovsky","doi":"10.1145/3099023.3099039","DOIUrl":"https://doi.org/10.1145/3099023.3099039","url":null,"abstract":"Authoring an adaptive educational system is a complex process that involves allocating a large range of educational content within a fixed sequence of units. In this paper, we describe Content Wizard, a concept-based recommender system for recommending learning materials that meet the instructor's pedagogical goals during the creation of an online programming course. Here, the instructors are asked to provide a set of code examples that jointly reflect the learning goals that are associated with each course unit. The Wizard is built on top of our course-authoring tool, and it helps to decrease the time instructors spend on the task and to maintain the coherence of the sequential structure of the course. It also provides instructors with additional information to identify content that might be not appropriate for the unit they are creating. We conducted an off-line study with data collected from an introductory Java course previously taught at the University of Pittsburgh in order to evaluate both the practicality and effectiveness of the system. We found that the proposed recommendation's performance is relatively close to the teacher's expectation in creating a computer-based adaptive course.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126409918","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}
Nowadays using E-learning platforms such as Intelligent Tutoring Systems (ITS) that support users to learn subjects are quite common. Despite the availability and the advantages of these systems, they ignore the learners' time limitation for learning a subject. In this paper we propose RUTICO, that recommends successful learning paths with respect to a learner's knowledge background and under a time constraint. RUTICO, which is an example of Long Term goal Recommender Systems (LTRS), after locating a learner in the course graph, it utilizes a Depth-first search (DFS) algorithm to find all possible paths for a learner given a time restriction. RUTICO also estimates learning time and score for the paths and finally, it recommends a path with the maximum score that satisfies the learner time restriction. In order to evaluate the ability of RUTICO in estimating time and score for paths, we used the Mean Absolute Error and Error. Our results show that we are able to generate a learning path that maximizes a learner's score under a time restriction.
如今，使用智能辅导系统(ITS)等支持用户学习科目的电子学习平台是相当普遍的。尽管这些系统具有可用性和优势，但它们忽略了学习者学习一门学科的时间限制。在本文中，我们提出了RUTICO，它根据学习者的知识背景和时间限制推荐成功的学习路径。RUTICO是长期目标推荐系统(Long Term goal Recommender Systems, LTRS)的一个例子，它在课程图中找到一个学习者后，利用深度优先搜索(deep -first search, DFS)算法，在给定的时间限制下，找到一个学习者的所有可能路径。RUTICO还会估计路径的学习时间和分数，最后，它会推荐一条满足学习者时间限制的分数最高的路径。为了评估RUTICO在估计路径时间和分数方面的能力，我们使用了平均绝对误差和误差。我们的结果表明，我们能够生成一个学习路径，在时间限制下最大化学习者的分数。
{"title":"RUTICO: Recommending Successful Learning Paths Under Time Constraints","authors":"A. Nabizadeh, A. Jorge, J. P. Leal","doi":"10.1145/3099023.3099035","DOIUrl":"https://doi.org/10.1145/3099023.3099035","url":null,"abstract":"Nowadays using E-learning platforms such as Intelligent Tutoring Systems (ITS) that support users to learn subjects are quite common. Despite the availability and the advantages of these systems, they ignore the learners' time limitation for learning a subject. In this paper we propose RUTICO, that recommends successful learning paths with respect to a learner's knowledge background and under a time constraint. RUTICO, which is an example of Long Term goal Recommender Systems (LTRS), after locating a learner in the course graph, it utilizes a Depth-first search (DFS) algorithm to find all possible paths for a learner given a time restriction. RUTICO also estimates learning time and score for the paths and finally, it recommends a path with the maximum score that satisfies the learner time restriction. In order to evaluate the ability of RUTICO in estimating time and score for paths, we used the Mean Absolute Error and Error. Our results show that we are able to generate a learning path that maximizes a learner's score under a time restriction.","PeriodicalId":219391,"journal":{"name":"Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization","volume":"7 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133204340","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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