Education and Learning Technologies
The UNISTUDIUM dataset contains the logs collected by Unistudium, the University of Perugia elearning platform based on moodle, a open source software for learning management systems (https://moodle.org).
The collected logs record interactions with the platform of students attending 4 courses during the time period of one semester, from 1st September to 31st December.
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To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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This csv provides the following:
- NeighbourNrInfo which indicates the RSSI recevied from the UE of the 5G stations (AP) 50, 51 or 52.
- RttInfo which indicates the RSSI recevied from the UE of the routers (AP) '3c:28:6d:b2:e2:0b', '3c:28:6d:b2:c9:1f' or '08:b4:b1:70:47:df'
- groundTruth indicates the position of the UE in that case
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This dataset contains 570 JPEG images of electricity meters taken from varied locations within the IIT BHU campus, including the GTFRC and residential apartments. It showcases a broad range of real-world scenarios, with each image demonstrating different challenges such as varying lighting conditions, levels of focus and clarity, and a wide range of capture angles. These attributes test and enhance the robustness of technologies designed to interpret meter readings from photographs under diverse conditions.
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This paper investigates the use of human-AI interaction in Chinese poetry education. Our work begins with semi-structured interviews with students, teachers, and AI experts to analyze the current difficulties in poetry education and highlight the application of AI in multimodal learning. Then, we design POEMaster, an AI-assisted interactive prototyping system that guides students in learning Chinese poetry. A between-subjects user study was conducted to examine the learning outcomes of POEMaster.
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This dataset contains complete information of the papers which are published in the area of Post Qunatum Cryptography (PQC). This dataset has been used to do the bibliometric analysis on the PQC feild to get the complere analysis results on that feild. This dataset has been downloaded fromt the Scopus database using Query related to the analysis work.
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The dataset was gathered from a virtual learning environment course at Constantine the Philosopher University in Nitra. It includes online activity logs of 152 university students enrolled in a blended Computer Science course during the winter semester from September 25, 2023, to December 21, 2023. This course combined traditional lectures and lab sessions with online interactions and digital access to course materials via the Learning Management System Moodle platform.
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The data and analysis of the surveys to study the users' opinion about the presence of an avatar during a learning experience in Mixed Reality. Also there are demographic data and the open questions collected. This data was used in the paper Evaluating the Effectiveness of Avatar-Based Collaboration in XR for Pump Station Training Scenarios for the GeCon 2024 Conference.
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The major language used on social media platforms is primarily dialectal, posing unique challenges for Natural Language Processing. To address this, a large, manually annotated corpus of approximately 30,500 Saudi dialect tweets in the food delivery app domain was introduced. The corpus was annotated with positive, negative, and neutral sentiment categories. Additionally, the existing SauDiSenti lexicon was expanded by 30%, providing an improved resource for sentiment analysis in the Saudi dialect. the corpus and expanded lexicon have been evaluated using machine learning classifiers.
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