2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)最新文献_第3页

A Novel Approach of Software Based Rubrics in Formative and Summative Assessment of Affective and Psycomotor Domains Among the Engineering Under Graduates: Focusing on Accrediation Process Across Pan India 一种基于软件的标准在工程本科毕业生情感和心理领域形成性和总结性评估中的新方法:关注整个泛印度的认证过程

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00108

S. Ahankari, Abhijitkumar A. Jadhav

{"title":"A Novel Approach of Software Based Rubrics in Formative and Summative Assessment of Affective and Psycomotor Domains Among the Engineering Under Graduates: Focusing on Accrediation Process Across Pan India","authors":"S. Ahankari, Abhijitkumar A. Jadhav","doi":"10.1109/ICALT.2018.00108","DOIUrl":"https://doi.org/10.1109/ICALT.2018.00108","url":null,"abstract":"Various statutory bodies across the globe are focusing on standardized assessment and evaluation process. Engineering graduate should gain specific sets of skills in cognitive, psychomotor and affective domain during the years of graduation. Accreditation process is to realize the valueaddition in transforming students admitted to the program into capable technocrats. Precise assessment and attainment of POs is a key factor in the accreditation process. As of total twelve POs recommended by NBA, India, majority of engineering institutes focus on assessment of four POs that belong to cognitive domain only. Direct assessment of cognitive domain is possible with conventional tools as it has proved its validity since ancient time with conventional examination pattern. For remaining eight POs, four in affective and psychomotor domain each; various assessment tools, it's methodology of assessment, authenticity, fractional weightage are required to arrive at realistic value of attainment for concern outcomes. This paper focuses on various new assessment tools and diverse formulae for calculation of attainment value of various POs come under the affective and psychomotor domain for more realistic number.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133121284","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}

引用次数: 1

Unobtrusive Students' Engagement Analysis in Computer Science Laboratory Using Deep Learning Techniques 基于深度学习技术的计算机科学实验室学生参与度分析

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00110

S. AshwinT., R. R. Guddeti

引用次数: 10

A Reinforcement Learning and Recurrent Neural Network Based Dynamic User Modeling System 基于强化学习和递归神经网络的动态用户建模系统

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00103

Abhishek Tripathi, S. AshwinT., R. R. Guddeti

{"title":"A Reinforcement Learning and Recurrent Neural Network Based Dynamic User Modeling System","authors":"Abhishek Tripathi, S. AshwinT., R. R. Guddeti","doi":"10.1109/ICALT.2018.00103","DOIUrl":"https://doi.org/10.1109/ICALT.2018.00103","url":null,"abstract":"With the exponential growth in areas of machine intelligence, the world has witnessed promising solutions to the personalized content recommendation. The ability of interactive learning agents to take optimal decisions in dynamic environments has been very well conceptualized and proven by Reinforcement Learning (RL). The learning characteristics of Deep-Bidirectional Recurrent Neural Networks (DBRNN) in both positive and negative time directions has shown exceptional performance as generative models to generate sequential data in supervised learning tasks. In this paper, we harness the potential of the said two techniques and strive to create personalized video recommendation through emotional intelligence by presenting a novel context-aware collaborative filtering approach where intensity of users' spontaneous non-verbal emotional response towards recommended video is captured through system-interactions and facial expression analysis for decision-making and video corpus evolution with real-time data streams. We take into account a user's dynamic nature in the formulation of optimal policies, by framing up an RL-scenario with an off-policy (Q-Learning) algorithm for temporal-difference learning, which is used to train DBRNN to learn contextual patterns and generate new video sequences for the recommendation. Evaluation of our system with real users for a month shows that our approach outperforms state-of-the-art methods and models a user's emotional preferences very well with stable convergence.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134556405","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}

引用次数: 3

Sentiment Analysis of Sub-Events Extracted Out of an Event Using Word2vec 基于Word2vec的事件提取子事件情感分析

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00105

B. N. Keshavamurthy, Shashank Srivastava, Jaseel Haris, Ankush Kumar, Seema V. Wazarkar

引用次数: 0

A Blueprint for a Blockchain-Based Architecture to Power a Distributed Network of Tamper-Evident Learning Trace Repositories 基于区块链的架构蓝图，为明显篡改学习跟踪存储库的分布式网络提供动力

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00059

Juan Carlos Farah, A. Vozniuk, M. Rodríguez-Triana, D. Gillet

{"title":"A Blueprint for a Blockchain-Based Architecture to Power a Distributed Network of Tamper-Evident Learning Trace Repositories","authors":"Juan Carlos Farah, A. Vozniuk, M. Rodríguez-Triana, D. Gillet","doi":"10.1109/ICALT.2018.00059","DOIUrl":"https://doi.org/10.1109/ICALT.2018.00059","url":null,"abstract":"The need to ensure privacy and data protection in educational contexts is driving a shift towards new ways of securing and managing learning records. Although there are platforms available to store educational activity traces outside of a central repository, no solution currently guarantees that these traces are authentic when they are retrieved for review. This paper presents a blueprint for an architecture that employs blockchain technology to sign and validate learning traces, allowing them to be stored in a distributed network of repositories without diminishing their authenticity. Our proposal puts participants in online learning activities at the center of the design process, granting them the option to store learning traces in a location of their choice. Using smart contracts, stakeholders can retrieve the data, securely share it with third parties and ensure it has not been tampered with, providing a more transparent and reliable source for learning analytics. Nonetheless, a preliminary evaluation found that only 56% of teachers surveyed considered tamper-evident storage a useful feature of a learning trace repository. These results motivate further examination with other end users, such as learning analytics researchers, who may have stricter expectations of authenticity for data used in their practice.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134629819","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}

引用次数: 24

Learning in Communities: How Do Outstanding Users Differ From Other Users? 社区学习:优秀用户与其他用户有何不同?

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00048

T. B. Procaci, S. Siqueira, B. Nunes

引用次数: 4

Words in Motion: Kinesthetic Language Learning in Virtual Reality 动态语言:虚拟现实中的动觉语言学习

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00069

C. Vazquez, Lei Xia, Takako Aikawa, P. Maes

{"title":"Words in Motion: Kinesthetic Language Learning in Virtual Reality","authors":"C. Vazquez, Lei Xia, Takako Aikawa, P. Maes","doi":"10.1109/ICALT.2018.00069","DOIUrl":"https://doi.org/10.1109/ICALT.2018.00069","url":null,"abstract":"Embodied theories of language propose that the way we communicate verbally is grounded in our body. Nevertheless, the way a second language is conventionally taught does not capitalize on kinesthetic modalities. The tracking capabilities of room-scale virtual reality systems afford a way to incorporate kinesthetic learning in language education. We present Words in Motion, a virtual reality language learning system that reinforces associations between word-action pairs by recognizing a student's movements and presenting the corresponding name of the performed action in the target language. Results from a user study involving 57 participants suggest that the kinesthetic approach in virtual reality has less immediate learning gain in comparison to a text-only condition and no immediate difference with participants in a non-kinesthetic virtual reality condition. However, virtual kinesthetic learners showed significantly higher retention rates after a week of exposure than all other conditions and higher performance than non-kinesthetic virtual reality learners. Positive correlation between the times a word-action pair was executed and the times a word was remembered by the subjects, supports that virtual reality can impact language learning by leveraging kinesthetic elements.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133973653","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}

引用次数: 47

Monitoring Student Frustration Level Using Blackbox Logs 使用黑匣子日志监测学生的沮丧程度

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00119

P. Kurtiker, R. Wagh

引用次数: 1

Promises and Constraints of Virtual Reality Integration: Perceptions from Pre-Service Teachers and K-12 Students 虚拟现实整合的承诺与约束:职前教师和K-12学生的感知

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00098

C. Chou, Daniel A. Hoisington

引用次数: 1

Fuzzy QFD for Decision Support Model in Evaluating Basic Cause of Children Falling Into Blue Whale Game 评价儿童陷入蓝鲸游戏基本原因的模糊QFD决策支持模型

2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2018-07-01 DOI: 10.1109/ICALT.2018.00032

Richa Pandey, T. Mukherjee

{"title":"Fuzzy QFD for Decision Support Model in Evaluating Basic Cause of Children Falling Into Blue Whale Game","authors":"Richa Pandey, T. Mukherjee","doi":"10.1109/ICALT.2018.00032","DOIUrl":"https://doi.org/10.1109/ICALT.2018.00032","url":null,"abstract":"Challenge Game to Death–Blue Whale. The era of intelligence and smartness has sometimes paved the way to success and sometimes to a tremendous set back or we can say downfall. But game's leading to death are a mischievous act rather we should say a sin. Those who fall into this often lose their life. Many cases of children especially teens have been into news and evidently correct that they were into the bold game of death and finally played with their lives. A fuzzy QFD pattern is being formulated here with the linguistic approach to interpret the basic causes why are our children getting up into these unwanted circumstances and becoming prey of it. This approach uses QFD as a transforming device to link factors with brain strategy and some interpretation to the final cause is formulated. A linguistic data has been taken after a survey from different people and units some belonging to academics, some to media, some to parents and some to children and local people and the HOQ (house of quality) is developed. The paper outlines the major parameters and their rankings as observed from the survey and linguistic data.","PeriodicalId":361110,"journal":{"name":"2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121687869","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}

引用次数: 3