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Learning Machine Learning: A Case Study

Niklas Lavesson
2010 IEEE Transactions on Education  
BACKGROUND Machine learning is the study of computer programs that improve automatically through experience [9] .  ...  The Machine Learning course at BTH is given at the advanced level and is featured in a number of computer science Master's programs.  ... 
doi:10.1109/te.2009.2038992 fatcat:4sih2rwiqzdkpk6ughyidtwloq

Teaching Computational Machine Learning (without Statistics)

Katherine M. Kinnaird
2020 Teaching Machine Learning Workshop  
Emphasizing the development of good habits of mind, this course trains students to be independent machine learning practitioners through an iterative, cyclical framework for teaching concepts while adding  ...  This paper presents an undergraduate machine learning course that emphasizes algorithmic understanding and programming skills while assuming no statistical training.  ...  Acknowledgements The author is the Clare Boothe Luce Assistant Professor of Computer Science and Statistical and Data Science at Smith College and as such, is supported by Henry Luce Foundation's Clare  ... 
dblp:conf/teachml/Kinnaird20 fatcat:j2l4taudgrf4hf3syuihaqw5gu

Identifying Factors for Master Thesis Completion and Non-completion Through Learning Analytics and Machine Learning [chapter]

Jalal Nouri, Ken Larsson, Mohammed Saqr
2019 Lecture Notes in Computer Science  
By applying traditional statistical methods (descriptive statistics, correlation tests and independent sample t-tests), as well as machine learning algorithms, we identify five central factors that can  ...  Can we predict completion and noncompletion of master thesis using such variables in order to optimise the matching of supervisors and students?  ...  To answer these research questions, we extracted data about supervisors and students from two thesis management systems, Daisy and SciPro from the Department of Computer and Systems Sciences, Stockholm  ... 
doi:10.1007/978-3-030-29736-7_3 fatcat:bn7rcntrszcwvf3kfy6dszjlyu

Learning Analytics [chapter]

2014 Encyclopedia of Social Network Analysis and Mining  
The canonical approach would be to compute the conditional probabilities and nd strong correlations, but as a machine learning exercise we took a dierent approach.  ...  As part of our development, we built a classication system to address the following question: Given student grades as labels and the features we have collected, can we predict students' grades without  ... 
doi:10.1007/978-1-4614-6170-8_100022 fatcat:hex3nvxwzrb4piin3scos4nqhe


Mahdiyah Al Muti'ah
2019 Journal of Mechanical Engineering and Vocational Education (JoMEVE)  
positive correlation between creativity learn students and computer laboratory facilities in a simultaneous manner with the achievement manufacture drawing practice students of grades XI students of machine  ...  Questionnaires are used to gather data independent </pre><pre>variable that was creativity learn students and computer laboratory facilities, </pre><pre>whereas documentation methods was used to gather  ...  Media use against Achievement Learning Accounting Trading company Grade XI Program Accounting Expertise SMK N 7 Yogyakarta 2014/2015 school year ".  ... 
doi:10.20961/jomeve.v1i2.25062 fatcat:oynbcymtibc7fmxpgnslza5nza

Assessing the Learning of Machine Learning in K-12: A Ten-Year Systematic Mapping

Marcelo Fernando Rauber, Christiane Gresse von Wangenheim
2022 Informatics in Education. An International Journal  
Yet, a question less considered is how to assess the learning of ML.  ...  The simplest assessments range from quizzes to performance-based assessments assessing the learning of basic ML concepts, approaches, and in some cases ethical issues and the impact of ML on lower cognitive  ...  Acknowledgments This work was supported by the CNPq (National Council for Scientific and Technological Development), a Brazilian government entity focused on scientific and technological development [Grant  ... 
doi:10.15388/infedu.2023.11 fatcat:dm6zy42usbez5fk7a26ykojhsm

A New Learning Path Model for E-Learning Systems

David Brito Ramos, Ilmara Monteverde Martins Ramos, Isabela Gasparini, Elaine Harada Teixeira de Oliveira
2021 International Journal of Distance Education Technologies  
Both tools were tested in a real environment, presenting useful results. The authors carried experiments with students from three programs: physics, electrical engineering, and computer science.  ...  This work presents a new approach to the learning path model in e-learning systems. The model uses data from the database records from an e-learning system and uses graphs as representation.  ...  the Computer Engineering program, where it was analyzed the interaction of group activities.  ... 
doi:10.4018/ijdet.20210401.oa2 fatcat:ugazuup32jerdllypssuumwqwu

Estimation of Success in Collaborative Learning Based on Multimodal Learning Analytics Features

Daniel Spikol, Emanuele Ruffaldi, Lorenzo Landolfi, Mutlu Cukurova
2017 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)  
The answer to the question provides ways to automatically identify the students at risk of not having success during the learning activities and provides means for different types of interventions to support  ...  the learning objects (like physical computing components or laboratory equipment).  ...  ACKNOWLEDGMENT The XXXX project has received funding from  ... 
doi:10.1109/icalt.2017.122 dblp:conf/icalt/SpikolRLC17 fatcat:ep5g6kpvwzbmdigs2r3xxrtewm

A system to grade computer programming skills using machine learning

Shashank Srikant, Varun Aggarwal
2014 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '14  
To the best of the authors' knowledge, this is the first time a system using machine learning has been developed and used for grading programs.  ...  These features are then used to learn a model to grade the programs, which are built against evaluations done by experts.  ...  Acknowledgment The authors would like to thank Vinay Shashidhar for his help in this work and for his invaluable suggestions.  ... 
doi:10.1145/2623330.2623377 dblp:conf/kdd/SrikantA14 fatcat:hgorlhf24zcspjdbbxkiiy2nai

A Machine Learning-based Recommender System for Improving Students Learning Experiences

Nacim Yanes, Ayman Mohamed Mostafa, Mohamed Ezz, Saleh N. Almuayqil
2020 IEEE Access  
The number of case studies is proportional to the number of case studies used in the course.  ...  system, using different machine learning algorithms, for predicting suitable actions to enhance the quality of the courses and thus to improve the overall educational program.  ...  Zhang His areas of interest include health informatics, knowledge discovery, knowledge management, digital transformation, and data science.  ... 
doi:10.1109/access.2020.3036336 fatcat:pdga6oa4yjf6thnazuxcxapxcy

Integrating Learning Analytics and Collaborative Learning for Improving Student's Academic Performance

Adnan Rafique, Muhammad Salman Khan, Muhammad Hasan Jamal, Mamoona Tasadduq, Furqan Rustam, Ernesto Lee, Patrick Bernard Washington, Imran Ashraf
2021 IEEE Access  
Overall, the study found that collaborative learning methods play a significant role to enhance the learning capability of the students.  ...  As a secondary part of this research, it also explores the potential of collaborative learning as an intervention to act in combination with the prediction system to improve the performance of students  ...  The dataset is collected from two independent MOOC-enabled Computer Science courses and contains the learners' interaction logs and assessment grades.  ... 
doi:10.1109/access.2021.3135309 fatcat:qlvmlzghrbcv7bc7narz3qc5hm

Can Machines Learn to Comprehend Scientific Literature?

Donghyeon Park, Yonghwa Choi, Daehan Kim, Minhwan Yu, Seongsoon Kim, Jaewoo Kang
2019 IEEE Access  
To measure the ability of a machine to understand professional-level scientific articles, we construct a scientific question answering task called PaperQA.  ...  The results indicate that the PaperQA task is the most difficult QA task for both humans (lay people) and machines (deep-learning models).  ...  To ensure the quality of our cloze-style questions, we have filtered all of the unusual cases to get rid of unclear and nonsense questions.  ... 
doi:10.1109/access.2019.2891666 fatcat:t35pl7o7pvdmhh2ehullgow2di

Supporting traditional educational process with e-learning tools

Zolt Namestovski, Marta Takacs, Branka Arsovic
2012 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics  
This paper presents several methods of using e-learning tools such as Moodle, the free and open-source Course Management System and WordPress, the platform for free publishing and blogging.  ...  In the last few years the role and the significance of the work forms supported with computers, networks and virtual environments increased.  ...  Programmed teaching involved programmed teaching material (textbook) and/or the implementation machine for learning and teaching.  ... 
doi:10.1109/sisy.2012.6339565 dblp:conf/sisy/NamestovskiTA12 fatcat:tlra7njkdjfdpbzfplbd6zxvlu

Predicting Cognitive Presence in At-Scale Online Learning: MOOC and For-Credit Online Course Environments

Jeonghyun Lee, Farahnaz Soleimani, India Irish, John Hosmer, IV, Meryem Yilmaz Soylu, Roy Finkelberg, Saurabh Chatterjee
2022 Online Learning  
We present a machine learning (ML) model which identifies the phase of cognitive presence exhibited by a student's post and suggest future applications of such a model to help online students develop higher-order  ...  We collect discussion forum transcript data from two online courses: CS1301 (an introductory computer programming MOOC) offered by edX and CS6601 (a graduate course on artificial intelligence) which uses  ...  The authors received approval from the ethics review board of the Georgia Institute of Technology, USA for this study.  ... 
doi:10.24059/olj.v26i1.3060 fatcat:ep437ismnzb5niu7ruizzrxunm

Loosely-Tied Distributed Architecture for Highly Scalable E-Learning System [chapter]

Gierlowski, Nowicki
2010 E-learning Experiences and Future  
to use e-learning systems, analysis of intelligent agents using e-learning, assessment methods for e-learning and barriers to use of effective e-learning systems in education.  ...  All possible mechanisms are moved to a system's server, while client side software is severely reduced and implemented by use of operating system independent WBTs (thinclient architecture).  ...  id, timeframe of test, client-side grading results of all questions and total grade, all answers, operating system computer name and user name, IP address etc.  ... 
doi:10.5772/8817 fatcat:fenjigihvnazjbc4ohkc6zfqqe
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