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Demir, Metin – Educational Sciences: Theory and Practice, 2015
This study predicts the number of correct answers given by pre-service classroom teachers in Civil Servant Recruitment Examination's (CSRE) educational sciences test based on their high school grade point averages, university entrance scores, and grades (mid-term and final exams) from their undergraduate educational courses. This study was…
Descriptors: Preservice Teachers, Scores, Artificial Intelligence, Grade Point Average
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Bone, Daniel; Goodwin, Matthew S.; Black, Matthew P.; Lee, Chi-Chun; Audhkhasi, Kartik; Narayanan, Shrikanth – Journal of Autism and Developmental Disorders, 2015
Machine learning has immense potential to enhance diagnostic and intervention research in the behavioral sciences, and may be especially useful in investigations involving the highly prevalent and heterogeneous syndrome of autism spectrum disorder. However, use of machine learning in the absence of clinical domain expertise can be tenuous and lead…
Descriptors: Clinical Diagnosis, Autism, Pervasive Developmental Disorders, Artificial Intelligence
Mills, Caitlin; D'Mello, Sidney – International Educational Data Mining Society, 2015
This paper reports the results from a sensor-free detector of mind wandering during an online reading task. Features consisted of reading behaviors (e.g., reading time) and textual features (e.g., level of difficulty) extracted from self-paced reading log files. Supervised machine learning was applied to two datasets in order to predict if…
Descriptors: Reading, Identification, Attention, Reading Rate
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Gabriel, Florence; Signolet, Jason; Westwell, Martin – International Journal of Research & Method in Education, 2018
Mathematics competency is fast becoming an essential requirement in ever greater parts of day-to-day work and life. Thus, creating strategies for improving mathematics learning in students is a major goal of education research. However, doing so requires an ability to look at many aspects of mathematics learning, such as demographics and…
Descriptors: Artificial Intelligence, Mathematics Instruction, Numeracy, Models
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Harteis, Christian; Fischer, Christoph; Töniges, Torben; Wrede, Britta – Frontline Learning Research, 2018
Preventing humans from committing errors is a crucial aspect of man-machine interaction and systems of computer assistance. It is a basic implication that those systems need to recognise errors before they occur. This paper reports an exploratory study that utilises eye-tracking technology and automated face recognition in order to analyse test…
Descriptors: Learning Processes, Error Patterns, Error Correction, Eye Movements
Cunningham, Dawn; Donahue, Michelle; Hambleton, Laura; Ross, Julia; Schmidt, Linda – Smithsonian Institution, 2018
This year's annual report features experts from across the Smithsonian whose work represents the best of innovation for the public good. They provide an excellent bird's-eye view of the many new approaches Smithsonian is taking, each with the goal of opening new opportunities for learning and discovery.
Descriptors: Museums, Heritage Education, Institutional Mission, Exhibits
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Lenat, Douglas B.; Durlach, Paula J. – International Journal of Artificial Intelligence in Education, 2014
We often understand something only after we've had to teach or explain it to someone else. Learning-by-teaching (LBT) systems exploit this phenomenon by playing the role of "tutee." BELLA, our sixth-grade mathematics LBT systems, departs from other LTB systems in several ways: (1) It was built not from scratch but by very slightly…
Descriptors: Artificial Intelligence, Knowledge Level, Mathematics Instruction, Teaching Methods
Kyrilov, Angelo; Noelle, David C. – International Association for Development of the Information Society, 2014
Information technology is now ubiquitous in higher education institutions worldwide. More than 85% of American universities use e-learning systems to supplement traditional classroom activities while some have started offering Massive Online Open Courses (MOOCs), which are completely online. An obvious benefit of these online tools is their…
Descriptors: Grading, Automation, Feedback (Response), Computer Science Education
Nikelshpur, Dmitry O. – ProQuest LLC, 2014
Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…
Descriptors: Artificial Intelligence, Networks, Computation, Topology
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Loeckx, Johan – International Review of Research in Open and Distributed Learning, 2016
The opinions on MOOCs go to extremes, covering a wide variety of topics, affecting economy, pedagogy, and computer science which makes it hard to keep oversight. Despite the many excellent research reports and articles, an overview of the bigger picture, providing a holistic qualitative summary of the different opinions, is still very welcome.…
Descriptors: Online Courses, Computer Science, Teaching Methods, Social Environment
Chahine, Firas Safwan – ProQuest LLC, 2012
Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…
Descriptors: Mathematics, Artificial Intelligence, Multivariate Analysis
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Taçgin, Zeynep; Arslan, Ahmet – Education and Information Technologies, 2017
The purpose of this study is to determine perception of postgraduate Computer Education and Instructional Technologies (CEIT) students regarding the concepts of Augmented Reality (AR), Virtual Reality (VR), Mixed Reality (MR), Augmented Virtuality (AV) and Mirror Reality; and to offer a table that includes differences and similarities between…
Descriptors: Graduate Students, Student Attitudes, Computer Science Education, Educational Technology
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Shirahama, Kimiaki; Grzegorzek, Marcin; Indurkhya, Bipin – Journal of Problem Solving, 2015
"Large-Scale Multimedia Retrieval" (LSMR) is the task to fast analyze a large amount of multimedia data like images or videos and accurately find the ones relevant to a certain semantic meaning. Although LSMR has been investigated for more than two decades in the fields of multimedia processing and computer vision, a more…
Descriptors: Information Retrieval, Multimedia Materials, Man Machine Systems, Cooperation
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Knight, Simon; Littleton, Karen – Journal of Learning Analytics, 2015
This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances…
Descriptors: Dialogs (Language), Data Collection, Data Analysis, Artificial Intelligence
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Frude, Neil; Jandric, Petar – E-Learning and Digital Media, 2015
This conversation focuses on a book published in 1983 that examined "animism," the tendency to regard non-living entities as living and sentient. "The Intimate Machine" suggested that animism will be fully exploited by artificial intelligence (AI) and robotics, generating artefacts that will engage the user in…
Descriptors: Artificial Intelligence, Robotics, Books, Interpersonal Relationship
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