Education and Learning Technologies

This dataset contains the experiment results for the article named "Influence of Gamification Elements on Explicit Motive Dispositions"

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100 Views

    Fast traslate Icon translate     Fast traslate Icon translate   Because this instructional material will be used for teaching in some way, Youtube will be used because it offers authentic and can allow learners to review and rebuild concepts for national sustainable education with a humanistic national standard. Students will be able to understand further educational programs, essential thinking systems, and standards aspects by watching the video transcriptions in the table below.

 

 

 

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113 Views

This dataset analyzes a survey delivered in 2019 to 259 experts in engineering education that asked them to forecast which information and communication technologies were most likely to impact the practice of engineering education based on the expert's discipline (electrical, electronics, mechanical, telecommunications engineering, computer science, etc.) and region.

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201 Views

This benchmark dataset accompanies an article paper titled ``Learning to Reuse Distractors to support Multiple Choice Question Generation in Education''. It contains a test of 298 educational questions covering multiple subjects & languages and a 77K multilingual pool of distractor vocabulary. The goal is for a given question to propose a list of relevant candidate distractors from the pool of distractors. 

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291 Views

This paper presents the data that is used in the article entitled “Decoding contextual factors differentiating adolescents’ high, average and low digital reading performance through machine learning methods”, which investigated the key contextual factors that synergistically differentiate high and low performers, high and average performers, and low and average performers in digital reading, through the utilization of machine learning methods, namely, support vector machine (SVM) and SVM recursive feature elimination (SVM-RFE).

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162 Views

# Student Test Results Prediction based on Learning Behavior: Learning Beyond Tests

Dataset Part A: The Goal is to predict Test Results, in the form of averaged correctness, averaged timespent in the test, based only on the learning history (learning  behavior records)

Dataset Part B: The objective is to predict the last test results, points and scores, based on the learning behavior records and the first test results.

# About the dataset

The raw data is provided by ALIN.ai where a large number of students participated in math learning and tests, online. 

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1041 Views

This dataset includes the experience integrating Didactic Videos within "Electrical Machines I" subject (BSc in Electrical Engineering from the School of Industrial, Aerospace and Audiovisual Engineering of Terrassa (ESEIAAT), Universitat Politècnica de Catalunya (UPC)).

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177 Views

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This article was results based on the interview phase in the English language 

course of even semester [the academic year 2021-2022] Institut Agama Kristen 

Negeri Ambon. The majority concern is how the students of English courses respond 

during even semester conducted. Moreover, only a few students are encouraged to 

finish their course with moderate achievement, and half of the students are stated on 

lower achievement following unconscious narration to be absent during English 

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201 Views

This article presents the details of the Cardinal RF (CardRF) dataset. CardRF is acquired to foster research in RF- based UAV detection and identification or RF fingerprinting. RF signals were collected from UAV controllers, UAV, Bluetooth, and Wi-Fi devices. Signals are collected at both visual line-of-sight and beyond-line-of-sight. The assumptions and procedure for the data acquisition are presented. A detailed explanation of how the data can be utilized is discussed. CardRF is over 65 GB in storage memory.

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6529 Views

Please cite the following paper when using this dataset:

N. Thakur, “A Large-Scale Dataset of Twitter Chatter about Online Learning during the Current COVID-19 Omicron Wave,” Journal of Data, vol. 7, no. 8, p. 109, Aug. 2022, doi: 10.3390/data7080109

Abstract

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925 Views

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