Education and Learning Technologies

Student learning willingness is the decisive factor for achieving the final learning outcomes in curriculum teaching. On the other hand, the final learning outcomes achieved by students in the curriculum are a true reflection of student learning willingness. This paper selects 6 types of theoretical teaching method data and 4 types of student engagement behavior data used in the teaching process of the "Computer Systems" course in the Software Engineering major of Information Engineering School in the academic years 2021, 2022, and 2023 as the basic data.


This dataset contains the 100 level first semester results of 229 students in South East University in Nigeria. The average score for each student is computed based on 8 courses offered in that semester. The dataset contains both the CA and Exam scores respectively. The CA amd Exam score were subsequently conveerted to percentage


This is the ASSISTment data that gathered in the school year 2009~2010. The skill builder data is provided.

Skill builder data is also called mastery learning data. This dataset is from skill builder (mastery learning) problem sets, in which a student is considered mastered a skill when meeting certain criterion (normally set to answered 3 questions correctly in a row), and no more questions will be given after mastery.


The dataset collected for the whole Quran; 114 sura (6236 ayah) recited by 35 Reciters (approximately 218000 audio files), downloaded from this website, the audio files downloaded in mp3 format, all the downloaded files based on the Hafs from A’asim narration, the dataset figure shows reciters names who participate in this dataset.



With the development of recommender systems (RS), several promising systems

have emerged, such as context-aware RS, multi-criteria RS, and group RS. However, the

education domain may not benefit from these developments due to missing information, such

as contexts and multiple criteria, in educational data sets. In this paper, we announce and

release an open data set for educational recommender systems. This data set includes not


Abstract: This paper explains a new interactive power meter achieved by TMS 320 a digital signal processing (DSP) technique that defines equation conditions. Q_x = √ { V_rms^2 ∑_(n=1)^∞〖( Qn Vn)^2 }〗 for the importance n harmonics. The definition of reactive current is useful because by reduces its value, while the maximum PF (power factor) can be obtained for non-genetic systems.


It is suggested to use zero crossing detectors to build a high-precision power-factor meter. Low pass filters are suggested to stop this error source after the influence of input signal distortion is examined. Based on the measurement of voltage, current, and power factor, this system is also proposed as a new type of power standard meter.


<p>Abstract – This paper shows an overview of the recent developments in the field of Electric Vehicles (EVs), the integration of EVs and Smart Cars, the battery technology and the power electronics in EVs.&nbsp;Over the past decades, the automotive industry has faced growing challenges, including environmental concerns and the finite amount of fuel resources that mainly includes petrol and diesel. In response to these challenges, Electric Vehicles (EVs) have emerged as sustainable alternative, promising reduced emissions and increased energy efficiency.


In the domain of Natural Language Processing (NLP), the English Writing Fluency Improvement for non-native speakers, particularly in academic contexts, poses significant challenges. While Sentence-level Revision (SentRev) endeavors to address this concern, the existing evaluation corpus, SMITH, falls short in offering a robust and comprehensive assessment of the task. To bridge this gap, our research offers a novel evaluation corpus generation scheme, leading to the creation of Ten-Country Non-native Academic English Corpus (TCNAEC).