153 research outputs found
A Bibliometric Overview of the IEEE Transactions on Learning Technologies
No full textIEEE Transactions on Learning Technologies (IEEE-TLT) is a leading journal in the fields of Computer Science and Educational Research with a focus on learning technologies. It published its first issue in 2008 and commemorated its 15th anniversary in 2022. Inspired by this event, this work provides a general lifetime overview of the journal using bibliometric indicators and science mapping analysis. The main objective is to provide a complete overview of the main components that have affected the journal. This analysis includes key factors such as the most cited articles and the leading authors, institutions, and countries for the journal, along with an insight into the publication and the citation structure. We use the Web of Science Core Collection database to analyze the bibliometric data and VOSviewer software to graphically map the bibliographic material using a bibliographic coupling, co-citation, and co-occurrence of author keywords. With this analysis, we gain a deeper understanding of how IEEE-TLT is connected to other journals and researchers across the globe and how it contributes to scientific communities. Results indicate that IEEE-TLT is a high-impact journal in Computer Science and Education and has been referenced by a wide range of authors, institutions, countries, and the main topics related to learning technologies from all over the world
Enhancing Electron Transfer and Stability of Screen-Printed Carbon Electrodes Modified with AgNP-Reduced Graphene Oxide Nanocomposite
No full textThis paper presents a reliable solution to enhance the electron transfer and stability of screen-printed carbon electrodes (SPCEs) for the direct detection of pathogenic bacteria. A nanocomposite of silver nanoparticles (AgNPs) and reduced graphene oxide (rGO) was used to modify the SPCEs. Herein, the nanocomposite was synthesized via a hydrothermal method and then characterized by physicochemical methods. The electron transfer rate and electrochemical properties of the AgNP-rGO nanocomposite-modified SPCEs were investigated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy. Measurements were performed for the detection of Salmonella bacteria without any labels. Results showed that the nanocomposite firmly adhered to the surfaces of the SPCEs, led to an increase of approximately 160% in the peak current, and decreased the charge transfer resistance to 0.45 kΩ. Electrochemical stability was found in 30 CV cycles. The modified SPCEs could detect Salmonella bacteria directly at concentrations of 10–105 CFU/mL, with a limit of detection (LoD) of as low as 22 CFU/mL. A possible mechanism was proposed to explain the enhanced electron transfer on the surface and the stability of the AgNP-rGO nanocomposite-modified SPCEs. The biosensor showed high stability, cost-effectiveness, and simplicity for the direct detection of pathogenic bacteria. Graphical Abstract: [Figure not available: see fulltext.
Expression levels of B7-H3 and TLT-2 in human oral squamous cell carcinoma
No full textThe aim of the present study was to investigate the role of immune regulatory molecules B7-H3 [also known as cluster of differentiation 276] and triggering receptor expressed on myeloid cell-like transcript-2 (TLT-2) in patients with oral squamous cell carcinoma (OSCC). Human OSCC samples were obtained from 76 patients (female, 32; male, 44; age range, 23-81 years; median age, 50.9 years) that underwent resection for OSCC at Peking University Shenzhen Hospital (Shenzhen, China) between 2007 and 2010. In addition, control oral mucosal samples were obtained from 76 healthy individuals (female, 36; male, 40; age range, 21-62 years; median age, 45.3 years) during wisdom tooth extraction. Protein and gene expression levels of B7-H3 and TLT-2 were determined by immunohistochemical analysis and reverse transcription-polymerase chain reaction (RT-PCR). In the healthy oral mucosa samples, B7-H3 expression was identified to be weak, while the expression of TLT-2 was only detected sporadically in the cell membrane and cytoplasm. By contrast, the two regulatory molecules were widely expressed in the aforementioned localizations in human OSCC specimens upon immunohistochemical examination. Furthermore, quantitative RT-PCR confirmed the presence of significantly higher B7-H3 and TLT-2 expression levels in OSCC specimens compared with the oral mucosa of healthy individuals. The significantly higher expression levels of B7-H3 and TLT-2 in human OSCC specimens may indicate an inhibitory role of these molecules in the antitumoral immune response. To investigate interactions between these two molecules and individual antitumoral immune response in OSCC patients, prospective clinical studies with an adequate sample size are required.Shenzhen Basic Research Foundation [JC201105201030A]; Guangdong Province Nature Science Foundation [S2012010010382]; Shenzhen Science and Research Innovation Foundation [JCY20130402114702120]SCI(E)[email protected]
AS Tallinna Linnatransport bus fleet comparative analysis
No full textKOKKUVÕTE
Käesolevas lõputöö eesmärk oli analüüsida TLT bussiveeremit. Lõputöös analüüsiti ainult ühte ettevõtet - TLT. TLT tegeleb Tallinna linna ühistranspordi tagamisega. TLT bussiveerem koosneb järgmistest bussiliikidest: diisel-, CNG- ja hübriidbuss.
Lõputöö tegemisel, kevad 2024, ajal ei olnud TLT-s kasutusele võetud veel elektribusse. Elektribussid võetakse kasutusele TLT-s 2024. aasta jooksul. Töö autor tõi võrdlusena välja töös ka elektribusside TCO, et tekiks võrdlusmoment hetkel kasutusesolevate tehnoloogiate ja tulevikus kasutuselevõetavate tehnoloogiate vahel.
Lõputöö käigus analüüsiti TLT poolt töö autorile edastatud andmeid bussiveeremi kohta. Lõputöö käigus läbiviidud analüüs näitas, et TLT bussiveerem koosneb kolmest erinevast bussiliigist.
Uurimistöö tulemusena selgus, et 2024. aastal TLT-s kasutusele tulevad elektribusside TCO on kõige kulukam. Elektribusside näol on tegemist uue tehnoloogia ja bussiliigi kasutuselevõtuga TLT-s. Elektribussidele vajaliku taristu loomine nõuab TLT-lt suuri rahalisi kulutusi. TLT-s olemasolevatele bussiliikidele on juba taristu loodud. Elektribussid on paraku praegusel hetkel ainus mõistlik ja töötav tehnoloogiline lahendus maailmas, mis vastab EL seatud kliimaeesmärkide nõuetele.
Jättes kõrvale EL kliimaeesmärgid, oleks kõige kuluefektiivsem bussiliik TLT bussiveeremis hübriidbuss, mis kasutab sama taristut diiselbussiga. Lõputöö analüüsi käigus selguski, et kõige kuluefektiivsem ja keskkonnasõbralikum bussiliik TLT bussiveeremis praegusel hetkel on hübriidbuss. Lõputöö autoril puuduvad andmed, et selgitada, miks on hübriidbusse ainult 44 tükki TLT bussiveeremi kasutusel olevast 542 bussist.
Lõputöö autori seisukohast oleks TLT-l otstarbekas omada bussiveeremis ühte bussiliiki, mitte nelja, nagu saab olema 2024. aastal. Bussiveeremit, kus on mitme tootja poolt toodetud bussid erinevate tehnoloogiatega, ei ole mõistlik ja otstarbekam üleval pidada.
Lõputöö autoril puudub ligipääs andmetele, et analüüsida põhjuseid, miks TLT bussiveerem on nii mitmekülgne kõige mõistlikum kevad 2024 seisuga on viia kogu bussiveerem üle hübriibussidele.SUMMARY
The purpose of this study was to analyze TLT bus fleet . Only one company - TLT - was analyzed during this study. TLT deals with the provision of public transport in the city of Tallinn. The TLT bus fleet consists of the following types of buses - diesel, CNG and hybrid buses.
In the spring of 2024, when this study was done, electric buses had not yet been introduced in TLT bus fleet. Electric buses will be introduced in TLT bus fleet in 2024. The author of the study also brought out the TCO of electric buses as a comparison in this study, so there is a moment of comparison between the technologies which are currently in use in bus fleet and the technologies that will be introduced in the future.
During this study, the data about the bus fleet was provided by TLT to the author. The analysis carried out during the study showed that TLT's bus fleet consists of three different types of buses.
As a result of the research conducted during the study, it turned out that the TCO of the electric buses that will be introduced in TLT in 2024 is the most expensive. Electric buses are new technology and a new type of bus in TLT bus fleet. Creating the necessary infrastructure for electric buses requires large financial expenses from TLT. The existing bus types in TLT already has an infrastructure. Unfortunately, electric buses are currently the only reasonable and working technological solution in the world that meets the requirements of the climate goals set by the EU.
Leaving aside EU climate goals, the most cost-effective bus type in TLT bus fleet would be a hybrid bus. Hybrid bus uses the same infrastructure as a diesel bus. During the analysis of the thesis, it became clear that the most cost-effective and environmentally friendly bus type in TLT's bus fleet currently is the hybrid bus.
The author of this study does not have the data to explain why there are only 44 hybrid buses in use out of the 542 buses used by the TLT bus fleet.
From the point of view of the author of this study, it would be expedient for TLT to have one type of bus in its bus fleet instead of four, as it is the case in 2024. It is not reasonable and practical to maintain a bus fleet with buses produced by several manufacturers with different technologies
Beyond personal transformation: Engaging students as agents for social change.
No full textAlthough Transformative Learning Theory (TLT) has been around for more than 40 years, few studies empirically engage critical theoretical frameworks to move beyond personal learning to identify the impacts of transformation on society. The purpose of this article is to discuss academic literature that expands TLT in the direction of societal transformation rather than merely personal change. Moreover, this article appeals for empirical studies that inform TLT through various socially constructed variables of race, class, (trans)gender, (a)sexuality, (dis)ability, and culture. The author titles this post-modern, intersectional approach critical social transformative learning theory
Capturing Movement: A Tablet App, Geometry Touch, for Recording Onscreen Finger-based Gesture Data
No full textThis paper presents a novel digital method of capturing finger-based gestures on touchscreen devices for the purposes of exploring tracing gestures in educational research. Given that tracing has been found to support cognition, learning and problem-solving in educational settings, data related to the performance of these gestures is increasingly of interest to researchers. Most educational research methods exploring the use of hand gestures rely on in-person data collection, whether through direct observation, or video recording of participants' behaviour for later analysis. These methods, while effective for observing gross movements, may not provide researchers with detailed insights into how learners interact with learning materials. Using custom tools to record touchscreen engagement on tablet computing devices can address this limitation, while also providing the means to visually represent touch-based interactions with these devices. Geometry Touch is an iPad app developed and tested by the primary author as part of a pilot study. The research study, theoretically grounded in Cognitive Load Theory, demonstrated that Geometry Touch could efficiently collect data on touchscreen interactions, while also providing potential avenues to quantify touchscreen interactions through computational means. The purpose of this paper is to report on the development and testing of this app, while providing an explanation of how it was used as a method of data collection by leveraging touchscreen technology. The paper concludes by discussing how this digital method of capturing movement can provide further insight into how finger-based gestures can influence learning and as such, could increase the reach of gesture-based research
Identifying Student Profiles Within Online Judge Systems Using Explainable Artificial Intelligence
No full textOnline Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an educational context such information may be deemed insufficient, it would be beneficial for both the student and the instructor to receive additional feedback about the overall development of the task. This work aims to tackle this limitation by considering the further exploitation of the information gathered by the OJ and automatically inferring feedback for both the student and the instructor. More precisely, we consider the use of learning-based schemes—particularly, Multi-Instance Learning and classical Machine Learning formulations—to model student behaviour. Besides, Explainable Artificial Intelligence is contemplated to provide human-understandable feedback. The proposal has been evaluated considering a case of study comprising 2,500 submissions from roughly 90 different students from a programming-related course in a Computer Science degree. The results obtained validate the proposal: the model is capable of significantly predicting the user outcome (either passing or failing the assignment) solely based on the behavioural pattern inferred by the submissions provided to the OJ. Moreover, the proposal is able to identify prone-to-fail student groups and profiles as well as other relevant information, which eventually serves as feedback to both the student and the instructor.This work has been partially funded by the “Programa Redes-I3CE de investigacion en docencia universitaria del Instituto de Ciencias de la Educacion (REDES-I3CE-2020-5069)” of the University of Alicante. The third author is supported by grant APOSTD/2020/256 from “Programa I+D+I de la Generalitat Valenciana”
ERP Markers of Implicit Sequence Learning
No full textFew studies investigate the within-trial temporal dynamics of neural processes related to implicit probabilistic sequence learning (IPSL). Those that do often use the electroencephalogram to measure and analyze event-related potentials (ERPs) linked to implicit learning. Presently, there is much debate about which ERP components capture processes related to IPSL. This is largely due to a lack of consensus concerning how to define ERPs using traditional methods. To address these concerns, the present dissertation examined the within-trial temporal dynamics of implicit learning using both a traditional and a new data-driven analysis (i.e. nonparametric cluster-based permutation tests) to analyze ERPs related to IPSL in a Triplets Learning Task (TLT). Results from the traditional analysis determined that cue-based expectancies learned via implicit associations during the TLT are distinguishable by differences in N400 amplitude. This finding was confirmed by the cluster-based analysis, which returned a significant late-occurring cluster that overlapped in time and space with the N400. This Late Cluster occurred after the average response-time and appeared to capture processes reflecting conflict resolution related to target predictability. The cluster-based analysis also returned an early-occurring cluster that was sensitive to target predictability but was not captured by the traditional analysis. This Early Cluster occurred before the onset of the average response-time and likely reflects response inhibition. Both Clusters demonstrated significant effects early in learning that diminish with practice on the TLT. This finding suggests that although early on participants react to unexpected events, with practice, participants learn to expect unlikely target events to occur occasionally. Taken together, the findings from the present dissertation demonstrate the temporal dynamics of within-trial processes during IPSL and implicate ERP markers of response inhibition and conflict resolution during the TLT. Additionally, these findings highlight discrepancies between the cluster-based and the traditional analysis, calling attention to the need to incorporate data-driven methods when investigating ERPs.Degree awarded: Ph.D. Psychology. The Catholic University of Americ
Adaptive Social Learning Based On Crowdsourcing
No full textMany techniques have been developed over the last several decades to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the Web and Adaptive Educational Hypermedia systems. While the web evolved into the next generation – Web 2.0 – enabling users to interact and collaborate with each other to create, organize and share knowledge via user-generated content, majority of e-learning systems do not utilize the power of their users to create high quality educational content and provide data for adaptive algorithms. In this paper, we introduce a novel social learning framework that allows anybody to author educational content in a form of mini-lessons, learn lessons by following adaptive learning pathways as well as interact with their peers as in a typical social network. The proposed approach combines concepts of crowdsourcing, online social networks and complex adaptive systems to engage users in efficient learning through teaching process. We first describe the main idea behind the framework and how users interact with it, and then we describe SALT system that implements the framework. We also performed evaluation of the SALT system via several classroom studies. Our results show that collective learning experiences can be efficiently utilized in adaptive social learning. We found that students tend to form stable clusters that survive very high similarity threshold. Meanwhile, our learning pathway analysis showed that almost all students have their own unique best pathway. Experiments with various recommendation algorithms showed that most algorithms obtain very small penalty in all classes
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