36,192 results
Search Results
102. A Learning Method for Automated Disassembly
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Wolff, Julius, Kolditz, Torge, Raatz, Annika, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Series Editor, Goedicke, Michael, Series Editor, Tatnall, Arthur, Series Editor, Neuhold, Erich J., Series Editor, Pras, Aiko, Series Editor, Tröltzsch, Fredi, Series Editor, Pries-Heje, Jan, Series Editor, Whitehouse, Diane, Series Editor, Reis, Ricardo, Series Editor, Furnell, Steven, Series Editor, Furbach, Ulrich, Series Editor, Winckler, Marco, Series Editor, Rauterberg, Matthias, Series Editor, and Ratchev, Svetan, editor
- Published
- 2019
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103. Artificial Intelligence Awareness in Work Environments
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Karvonen, Hannu, Heikkilä, Eetu, Wahlström, Mikael, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Series Editor, Goedicke, Michael, Series Editor, Tatnall, Arthur, Series Editor, Neuhold, Erich J., Series Editor, Pras, Aiko, Series Editor, Tröltzsch, Fredi, Series Editor, Pries-Heje, Jan, Series Editor, Whitehouse, Diane, Series Editor, Reis, Ricardo, Series Editor, Furnell, Steven, Series Editor, Furbach, Ulrich, Series Editor, Winckler, Marco, Series Editor, Rauterberg, Matthias, Series Editor, Barricelli, Barbara Rita, editor, Roto, Virpi, editor, Clemmensen, Torkil, editor, Campos, Pedro, editor, Lopes, Arminda, editor, Gonçalves, Frederica, editor, and Abdelnour-Nocera, José, editor
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- 2019
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104. Automation in Experimentation with Constructive Simulation
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Hodicky, Jan, Prochazka, Dalibor, Prochazka, Josef, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, and Mazal, Jan, editor
- Published
- 2019
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105. Valmet Supplies Key Technology for Shandong Jin Tian He Paper's Board Machine.
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PAPER industry , *AUTOMATION , *DNA machinery , *SALES executives - Published
- 2024
106. Desirable and Realistic Futures of the University: A Mixed-Methods Study with Teachers in Denmark
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Magda Pischetola, Maria Hvid Stenalt, Liv Nøhr, Danielle Elizabeth Hagood, and Morten Misfeldt
- Abstract
In this paper, we put in dialogue the local dimension of a nation-state with the global challenges faced by universities worldwide. We focus on the case of Denmark, a nation that was exceptionally active in implementing international university reforms and where digitalisation is a high priority of the public sector governance. The article seeks to contribute to speculative research and critical studies by presenting a mixed-methods study that explores higher education teachers' views about desirable and realistic future scenarios in Denmark. The study draws on data from a survey applied at a large Danish university, analysed both quantitatively (N = 755) and qualitatively (N = 53). The findings show that teachers share clusters of concern about uncontrolled digitalisation and teaching automation, commodification of education, and modularisation of university courses, the latter being a contested but realistic perspective in the latest political reforms. They reaffirm the mission of the university as preparing students for solving real problems and contributing to the challenges of the present time. The paper concludes with a call for university management to recalibrate future imaginaries to the values expressed by the teachers, and the university they wish to create.
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- 2024
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107. Secure Dematerialization of Assessments in Digital Universities through Moodle, WebRTC and Safe Exam Browser (SEB)
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International Association for Development of the Information Society (IADIS), Sylla, Khalifa, Babou, Birahim, and Ouya, Samuel
- Abstract
This paper deals with a solution allowing digital universities to extend the functionalities of their distance learning platform to offer a secure solution for the dematerialization of assessments. Currently we are witnessing the rise of digital universities, this is the case in Africa, particularly in Senegal. We are witnessing strong growth in the number of students, in a context of extension and diversification of training offers. This is the case of the Virtual University of Senegal (UVS), the number of students has increased from 2,000 students in 2013, the year of its creation, to 50,000 in 2021. It offers 13 licenses and 30 courses of training. With these large numbers, the organization of assessments in these universities becomes more and more tedious. Taking the example of the UVS with 50,000 students and 30 training courses, we will have to deploy millions of exams copies due to one copy per candidate. These universities have digital campuses (connected campuses) or Open Digital Spaces (ENO) which make it possible to organize face-to-face evaluations on the table. This organization has several disadvantages, on the one hand, the management of the proofs and the correction of the copies require the mobilization of human and financial resources; on the other hand, the risks of errors, reports and authenticity of the notes. In this article, we propose a secure system for managing online assessments in digital universities based on LMS Moodle, SEB and remote monitoring with the JITSI video conferencing system. The solution will allow universities to optimize human and financial resources and make assessment results more reliable.
- Published
- 2022
108. DerSql, Generating SQL from an Entity-Relation Diagram
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Andrea Domínguez-Lara and Wulfrano Arturo Luna-Ramírez
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The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the problem of how to obtain code from a graphic representation, for instance an UML diagram or a Relational Diagram. Some advantages of automatic code generation are: a) to obtain the source code more quickly and to do it with lower margins of error; b) it is promising to be applied in teaching contexts, whilst provide instructors with a tool to teach, the expected results of assignments can be assessed by comparing the results of students and the automatic generated code. Furthermore, one of the most frequently tasks in classrooms when teaching relational databases is the design of Entity-Relationship Diagrams which eventually become SQL code. The manual transition from an Entity-Relationship Diagram to SQL code is a time-consuming process and requires of a skilled eye to be successfully performed. In this paper, we present "DerSql," an extension of the DIA Diagrammer, a well-known free software engineering tool, to automatically generate SQL code from an Entity-Relationship Diagrams. The results are tested for the case of 1 -- 1 and 1 -- n arities relationships. We consider that "DerSql" represents a remarkable tool for teaching while it is a promising advance in developing DIA as a 4th Generation software engineering application. [For the full proceedings, see ED638044.]
- Published
- 2022
109. An IOT Based Smart Shopping Cart for Smart Shopping
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Karjol, Srinidhi, Holla, Anusha K., Abhilash, C. B., Barbosa, Simone Diniz Junqueira, Series Editor, Chen, Phoebe, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Nagabhushan, T.N., editor, Aradhya, V. N. Manjunath, editor, Jagadeesh, Prabhudev, editor, Shukla, Seema, editor, and M.L., Chayadevi, editor
- Published
- 2018
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110. Complex Industrial Systems Automation Based on the Internet of Things Implementation
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Kondratenko, Yuriy, Kozlov, Oleksiy, Korobko, Oleksiy, Topalov, Andriy, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Bassiliades, Nick, editor, Ermolayev, Vadim, editor, Fill, Hans-Georg, editor, Yakovyna, Vitaliy, editor, Mayr, Heinrich C., editor, Nikitchenko, Mykola, editor, Zholtkevych, Grygoriy, editor, and Spivakovsky, Aleksander, editor
- Published
- 2018
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111. Towards Semantic Reasoning in Knowledge Management Systems
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Mehdi, Gulnar, Brandt, Sebastian, Roshchin, Mikhail, Runkler, Thomas, Rannenberg, Kai, Editor-in-Chief, Sakarovitch, Jacques, Series Editor, Goedicke, Michael, Series Editor, Tatnall, Arthur, Series Editor, Neuhold, Erich J., Series Editor, Pras, Aiko, Series Editor, Tröltzsch, Fredi, Series Editor, Pries-Heje, Jan, Series Editor, Whitehouse, Diane, Series Editor, Reis, Ricardo, Series Editor, Furnell, Steven, Series Editor, Furbach, Ulrich, Series Editor, Winckler, Marco, Series Editor, Rauterberg, Matthias, Series Editor, Mercier-Laurent, Eunika, editor, and Boulanger, Danielle, editor
- Published
- 2018
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112. Auto Generation of Diagnostic Assessments and Their Quality Evaluation
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Dhavala, Soma, Bhatia, Chirag, Bose, Joy, Faldu, Keyur, and Avasthi, Aditi
- Abstract
A good diagnostic assessment is one that can (i) discriminate between students of different abilities for a given skill set, (ii) be consistent with ground truth data and (iii) achieve this with as few assessment questions as possible. In this paper, we explore a method to meet these objectives. This is achieved by selecting questions from a question database and assembling them to create a diagnostic test paper according to a given configurable policy. We consider policies based on multiple attributes of the questions such as discrimination ability and behavioral parameters, as well as a baseline policy. We develop metrics to evaluate the policies and perform the evaluation using historical student attempt data on assessments conducted on an online learning platform, as well as on a pilot test on the platform administered to a subset of users. We are able to estimate student abilities 40% better with a diagnostic test as compared to baseline policy, with questions derived from a larger dataset. Further, empirical data from a pilot gave an 18% higher spread, denoting better discrimination, for our diagnostic test compared to the baseline test. [For the full proceedings, see ED607784.]
- Published
- 2020
113. Claim Detection and Relationship with Writing Quality
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Wan, Qian, Crossley, Scott, Allen, Laura, and McNamara, Danielle
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In this paper, we extracted content-based and structure-based features of text to predict human annotations for claims and nonclaims in argumentative essays. We compared Logistic Regression, Bernoulli Naive Bayes, Gaussian Naive Bayes, Linear Support Vector Classification, Random Forest, and Neural Networks to train classification models. Random Forest and Neural Network classifiers yielded the most balanced identifications of claims and non-claims based on the evaluation of accuracy, precision, and recall. The Random Forest model was then used to calculate the number, percentage, and positionality of claims and non-claims in a validation corpus that included human ratings of writing quality. Correlational and regression analyses indicated that the number of claims and the average position of non-claims in text were significant indicators of essay quality in the expected direction. [This paper was published in: V. Cavalli-Sforza, C. Romero, A. Rafferty, & J. R. Whitehill (Eds.), "Proceedings of the 13th International Conference on Educational Data Mining (EDM)" (pp. 691-695). Virtual Conference: International Educational Data Mining Society.]
- Published
- 2020
114. Upskilling towards automation: a conversation with the experts
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Murphy, Liam
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- 2024
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115. Performance Evaluation of RPL Routing Protocol for IoT Based Power Distribution Network
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Tom, Rijo Jackson, Sankaranarayanan, Suresh, Barbosa, Simone Diniz Junqueira, Series Editor, Chen, Phoebe, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Bhattacharyya, Pushpak, editor, Sastry, Hanumat G., editor, Marriboyina, Venkatadri, editor, and Sharma, Rashmi, editor
- Published
- 2018
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116. Unity Application Testing Automation with Appium and Image Recognition
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Mozgovoy, Maxim, Pyshkin, Evgeny, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Itsykson, Vladimir, editor, Scedrov, Andre, editor, and Zakharov, Victor, editor
- Published
- 2018
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117. Intelligent Diagnostics of Mechatronic System Components of Career Excavators in Operation
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Malafeev, S. I., Malafeev, S. S., Tikhonov, Y. V., Kacprzyk, Janusz, Series editor, Kryzhanovsky, Boris, editor, Dunin-Barkowski, Witali, editor, and Redko, Vladimir, editor
- Published
- 2018
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118. Automatic Inventory of Multi-part Kits Using Computer Vision
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Rodríguez-Garrido, A. J., Quesada-Arencibia, A., Rodríguez-Rodríguez, J. C., García, C. R., Moreno-Díaz jr, R., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor
- Published
- 2018
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119. Proceedings of the International Conference on Educational Data Mining (EDM) (16th, Bengaluru, India, July 11-14, 2023)
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International Educational Data Mining Society, Feng, Mingyu, Käser, Tanja, and Talukdar, Partha
- Abstract
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for amplifying human potential." Not all students or seekers of knowledge receive the education necessary to help them realize their full potential, be it due to a lack of resources or lack of access to high quality teaching. The dearth in high-quality educational content, teaching aids, and methodologies, and non-availability of objective feedback on how they could become better teachers, deprive our teachers from achieving their full potential. The administrators and policy makers lack tools for making optimal decisions such as optimal class sizes, class composition, and course sequencing. All these handicap the nations, particularly the economically emergent ones, who recognize the centrality of education for their growth. EDM-2023 has striven to focus on concepts, principles, and techniques mined from educational data for amplifying the potential of all the stakeholders in the education system. The spotlights of EDM-2023 include: (1) Five keynote talks by outstanding researchers of eminence; (2) A plenary Test of Time award talk and a Banquet talk; (3) Five tutorials (foundational as well as advanced); (4) Four thought provoking panels on contemporary themes; (5) Peer reviewed technical paper and poster presentations; (6) Doctoral students consortium; and (7) An enchanting cultural programme. [Individual papers are indexed in ERIC.]
- Published
- 2023
120. Crowdsourcing Complex Task Automatically by Workflow Technology
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Zheng, Qiang, Wang, Wenyan, Yu, Yang, Pan, Maolin, Shi, Xiaohui, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Cao, Jian, editor, and Liu, Jianxun, editor
- Published
- 2017
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121. System Architecture for Personalized Automatic Audio-Visual Content Generation from Web Feeds to an iTV Platform
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Silva, Carlos, Campelo, David, Silva, Telmo, Silva, Valter, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Abásolo, María José, editor, Almeida, Pedro, editor, and Pina Amargós, Joaquín, editor
- Published
- 2017
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122. 西门子S7-200在纸品传送设备上的应用调试.
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王召彦
- Subjects
PAPER arts ,PAPER products ,AUTOMATION ,PACKAGING - Abstract
Copyright of China Pulp & Paper Industry is the property of China Pulp & Paper Industry Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
- Published
- 2023
123. Product Knowledge Management Support for Customer-Oriented System Configuration
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Smirnov, Alexander, Shilov, Nikolay, Oroszi, Andreas, Sinko, Mario, Krebs, Thorsten, van der Aalst, Wil M.P., Series editor, Mylopoulos, John, Series editor, Rosemann, Michael, Series editor, Shaw, Michael J., Series editor, Szyperski, Clemens, Series editor, and Abramowicz, Witold, editor
- Published
- 2017
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124. Automated Chest X-ray Image View Classification using Force Histogram
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Santosh, K. C., Wendling, Laurent, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Santosh, K.C., editor, Hangarge, Mallikarjun, editor, Bevilacqua, Vitoantonio, editor, and Negi, Atul, editor
- Published
- 2017
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125. Review on Paper Cup Manufacturing Process for Industry Automation
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Nikhil Zade
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Engineering ,business.product_category ,business.industry ,Manufacturing process ,Paper cup ,business ,Automation ,Manufacturing engineering - Published
- 2021
126. A Framework for Measuring Relevancy in Discovery Environments: Increasing Scalability and Reproducibility.
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Galbreath, Blake, Merrill, Alex, and Johnson, Corey M.
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WORLD Wide Web ,SERIAL publications ,ECOLOGY ,COMPUTER software ,SEASONS ,RESEARCH evaluation ,CITATION analysis ,NEWSPAPERS ,STUDENTS ,BIBLIOGRAPHICAL citations ,BOOKS ,BIBLIOGRAPHY ,MEDICAL research ,AUTOMATION ,DATA analysis software - Abstract
Institutional discovery environments now serve as central resource databases for researchers in the academic environment. Over the last several decades, there have been numerous discovery layer research inquiries centering primarily on user satisfaction measures of discovery system effectiveness. This study focuses on the creation of a largely automated method for evaluating discovery layer quality, utilizing the bibliographic sources from student research projects. Building on past research, the current study replaces a semiautomated Excel Fuzzy Lookup Add-In process with a fully scripted R-based approach, which employs the stringdist R package and applies the Jaro-Winkler distance metric as the matching evaluator. The researchers consider the error rate incurred by relying solely on an automated matching metric. They also use Open Refine for normalization processes and package the tools together on an OSF site for other institutions to use. Since the R-based approach does not require special processing or time and can be reproduced with minimal effort, it will allow future studies and users of our method to capture larger sample sizes, boosting validity. While the assessment process has been streamlined and shows promise, there remain issues in establishing solid connections between research paper bibliographies and discovery layer use. Subsequent research will focus on creating alternatives to paper titles as search proxies that better resemble genuine information-seeking behavior and comparing undergraduate and graduate student interactions within discovery environments. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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127. Human performance and automated operations: a regulatory perspective.
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Bergh LIV, Teigen KS, and Dørum F
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- Humans, Norway, Ergonomics, Digital Technology, Oil and Gas Industry, Automation
- Abstract
Increased levels of digitalisation present major opportunities for efficiency in the oil and gas industry but can also contribute to new risks and vulnerabilities. Based on developments in the industry, the Norwegian Ocean Industry Authority (HAVTIL) has in recent years pursued targeted knowledge development and follow-up of company's digitalisation initiatives. This paper explores data collected through HAVTIL's audits of the development and use of automated systems within well operations. The analysis of the data resulted in the identification of five main topics related to the implementation of digital technologies. The five main topics were organisational complexity, follow-up and implementation of technology, analysis and documentation, user-interface and alarms and competence and training. Overall, the results support research findings within human factors and technology development, pointing out that there is a lack of focus on human factors in both development projects and in operations. In addition, this paper provides insight into how digitalisation initiatives are followed-up and explores the results from the analysis in light of the current developments in the industry.
- Published
- 2024
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128. Automated multiclass segmentation, quantification, and visualization of the diseased aorta on hybrid PET/CT-SEQUOIA.
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van Praagh GD, Nienhuis PH, Reijrink M, Davidse MEJ, Duff LM, Spottiswoode BS, Mulder DJ, Prakken NHJ, Scarsbrook AF, Morgan AW, Tsoumpas C, Wolterink JM, Mouridsen KB, Borra RJH, Sinha B, and Slart RHJA
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- Humans, Aorta diagnostic imaging, Aortic Diseases diagnostic imaging, Female, Feasibility Studies, Male, Positron Emission Tomography Computed Tomography, Image Processing, Computer-Assisted methods, Automation
- Abstract
Background: Cardiovascular disease is the most common cause of death worldwide, including infection and inflammation related conditions. Multiple studies have demonstrated potential advantages of hybrid positron emission tomography combined with computed tomography (PET/CT) as an adjunct to current clinical inflammatory and infectious biochemical markers. To quantitatively analyze vascular diseases at PET/CT, robust segmentation of the aorta is necessary. However, manual segmentation is extremely time-consuming and labor-intensive., Purpose: To investigate the feasibility and accuracy of an automated tool to segment and quantify multiple parts of the diseased aorta on unenhanced low-dose computed tomography (LDCT) as an anatomical reference for PET-assessed vascular disease., Methods: A software pipeline was developed including automated segmentation using a 3D U-Net, calcium scoring, PET uptake quantification, background measurement, radiomics feature extraction, and 2D surface visualization of vessel wall calcium and tracer uptake distribution. To train the 3D U-Net, 352 non-contrast LDCTs from (2-[
18 F]FDG and Na[18 F]F) PET/CTs performed in patients with various vascular pathologies with manual segmentation of the ascending aorta, aortic arch, descending aorta, and abdominal aorta were used. The last 22 consecutive scans were used as a hold-out internal test set. The remaining dataset was randomly split into training (n = 264; 80%) and validation (n = 66; 20%) sets. Further evaluation was performed on an external test set of 49 PET/CTs. The dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to assess segmentation performance. Automatically obtained calcium scores and uptake values were compared with manual scoring obtained using clinical softwares (syngo.via and Affinity Viewer) in six patient images. intraclass correlation coefficients (ICC) were calculated to validate calcium and uptake values., Results: Fully automated segmentation of the aorta using a 3D U-Net was feasible in LDCT obtained from PET/CT scans. The external test set yielded a DSC of 0.867 ± 0.030 and HD of 1.0 [0.6-1.4] mm, similar to an open-source model with a DSC of 0.864 ± 0.023 and HD of 1.4 [1.0-1.8] mm. Quantification of calcium and uptake values were in excellent agreement with clinical software (ICC: 1.00 [1.00-1.00] and 0.99 [0.93-1.00] for calcium and uptake values, respectively)., Conclusions: We present an automated pipeline to segment the ascending aorta, aortic arch, descending aorta, and abdominal aorta on LDCT from PET/CT and to accurately provide uptake values, calcium scores, background measurement, radiomics features, and a 2D visualization. We call this algorithm SEQUOIA (SEgmentation, QUantification, and visualizatiOn of the dIseased Aorta) and is available at https://github.com/UMCG-CVI/SEQUOIA. This model could augment the utility of aortic evaluation at PET/CT studies tremendously, irrespective of the tracer, and potentially provide fast and reliable quantification of cardiovascular diseases in clinical practice, both for primary diagnosis and disease monitoring., (© 2024 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)- Published
- 2024
- Full Text
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129. Will visual cues help alleviating motion sickness in automated cars? A review article.
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Emond W, Bohrmann D, and Zare M
- Subjects
- Humans, Automobile Driving, Visual Perception, Motion Sickness prevention & control, Cues, Automobiles, Automation
- Abstract
This paper examines the feasibility of incorporating visual cueing systems within vehicles to mitigate the risk of experiencing motion sickness. The objective is to enhance passenger awareness and the ability to anticipate the forces associated with car travel motion. Through a comprehensive literature review, the findings demonstrate that visual cues can mitigate motion sickness for particular in-vehicle configurations, whereas their influence on situational awareness is not clear yet. Each type of visual cue proved more effective when presented in the peripheral field of view rather than solely in the central vision. Promising applications can be found within interactive screens and ambient lighting, while the use of extended reality shows potential for future investigations. In addition, integrating such systems into highly automated vehicles shows potential to improve their overall user acceptance.
- Published
- 2024
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130. Behavioral Insights: The Problem of Control in Education Governance
- Author
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Bruce Moghtader
- Abstract
This article offers a historical inquiry into behaviorism and its impact on standard of judgement concerning education policies. Drawing from Aldous Huxley's reservation towards behaviorism as a scientific movement that naturalizes the role of control in human affairs, the paper maps the impact of behaviorism on economics of education. By tracing the influence of behaviorism in both rational (human capital theory) and quasi-rational (behavioral insight) economics, we draw attention to the activity of knowledge-making that describes and prescribes agency. The paper demonstrates how policy instruments and outcomes are intimately linked to assumptions about personhood, and in the case of behavioral insight, they contribute to the scope of decision-making entrusted to government and business. Utilizing a genealogical approach, the paper invites ethical reflections on the long-term implications of behavioral economics in light of automation.
- Published
- 2024
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131. It Is Like a Friend to Me: Critical Usage of Automated Feedback Systems by Self-Regulating English Learners in Higher Education
- Author
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Long Li and Mira Kim
- Abstract
This paper explores international students' engagement with educational technology for self-regulated English learning at an Australian university. Despite the increased use of automated feedback systems (AFSs) for language assessment, students' critical engagement with them for independent learning remains under-researched. The study primarily employed a qualitative approach to understand the students' preferred AFS tools and critical engagement throughout their personalised learning journeys but it also included a small-scale quantitative component. Data were gathered from seven students' e-portfolios, focus group interviews as well as a survey among 32 participants. Results highlight positive perceptions and successful use of AFSs, with students leveraging these tools to identify improvement areas, track progress and gain confidence. The study emphasises the importance of course structure, teacher guidance and a combination of human and automated feedback, in fostering learner autonomy and emotional self-regulation. The paper underscores the potential for sustained use of AFSs beyond the cours, and the significance of guiding learners to critically use these tools for ongoing learning and growth rather than dependence. These findings have significant implications, as readily available artificial intelligence tools such as ChatGPT hold great pedagogical potential for self-regulated learning within and beyond the language learning field.
- Published
- 2024
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132. How Hard Can This Question Be? An Exploratory Analysis of Features Assessing Question Difficulty Using LLMs
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Andreea Dutulescu, Stefan Ruseti, Mihai Dascalu, and Danielle S. McNamara
- Abstract
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This study tackles the task of automated question difficulty assessment, exploring the potential of leveraging Large Language Models (LLMs) to enhance the comprehension of the context and interconnections required to address a question. Our method incorporates multiple LLM-based difficulty measures and compares their performance on the FairytaleQA educational dataset with the human-annotated difficulty labels. Besides comparing different computational methods, this study also bridges the gap between machine and human understanding of question difficulty by analyzing the correlation between LLM-based measures and human perceptions. Our results provide valuable insights into the capabilities of LLMs in educational settings, particularly in the context of reading comprehension.
- Published
- 2024
133. Automated Data Analysis of Unstructured Grey Literature in Health Research: A Mapping Review
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Lena Schmidt, Saleh Moham, Nick Meader, Jaume Bacardit, and Dawn Craig
- Abstract
The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or tools for health-related grey literature and soft data, with a focus on (semi)automating horizon scans, health technology assessments (HTA), evidence maps, or other literature reviews. We searched six databases to cover both health- and computer-science literature. After deduplication, 10% of the search results were screened by two reviewers, the remainder was single-screened up to an estimated 95% sensitivity; screening was stopped early after screening an additional 1000 results with no new includes. All full texts were retrieved, screened, and extracted by a single reviewer and 10% were checked in duplicate. We included 84 papers covering automation for health-related social media, internet fora, news, patents, government agencies and charities, or trial registers. From each paper, we extracted data about important functionalities for users of the tool or method; information about the level of support and reliability; and about practical challenges and research gaps. Poor availability of code, data, and usable tools leads to low transparency regarding performance and duplication of work. Financial implications, scalability, integration into downstream workflows, and meaningful evaluations should be carefully planned before starting to develop a tool, given the vast amounts of data and opportunities those tools offer to expedite research.
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- 2024
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134. Automated Grading and Feedback Tools for Programming Education: A Systematic Review
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Marcus Messer, Neil C. C. Brown, Michael Kölling, and Miaojing Shi
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We conducted a systematic literature review on automated grading and feedback tools for programming education. We analysed 121 research papers from 2017 to 2021 inclusive and categorised them based on skills assessed, approach, language paradigm, degree of automation, and evaluation techniques. Most papers assess the correctness of assignments in object-oriented languages. Typically, these tools use a dynamic technique, primarily unit testing, to provide grades and feedback to the students or static analysis techniques to compare a submission with a reference solution or with a set of correct student submissions. However, these techniques' feedback is often limited to whether the unit tests have passed or failed, the expected and actual output, or how they differ from the reference solution. Furthermore, few tools assess the maintainability, readability, or documentation of the source code, with most using static analysis techniques, such as code quality metrics, in conjunction with grading correctness. Additionally, we found that most tools offered fully automated assessment to allow for near-instantaneous feedback and multiple resubmissions, which can increase student satisfaction and provide them with more opportunities to succeed. In terms of techniques used to evaluate the tools' performance, most papers primarily use student surveys or compare the automatic assessment tools to grades or feedback provided by human graders. However, because the evaluation dataset is frequently unavailable, it is more difficult to reproduce results and compare tools to a collection of common assignments.
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- 2024
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135. Automation, Agencies and Aesthetics: The Politics of Data Visualizations in Configuring Teachers' Expertise
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Helene Friis Ratner
- Abstract
It is well-known that digital learning materials influence the classroom curriculum and didactics. At the same time, few studies examine the role of the data visualizations offered by digital learning materials. Data visualizations signpost the emergence of students as data subjects who can be observed and compared on a computer screen. They thus shape teachers' socio-technical ways of seeing student learning and are likely to influence student assessments. Drawing inspiration from Science and Technology Studies (STS), this paper advances an analytical framework for eliciting the politics of data visualizations, focusing on automation, agencies, and aesthetics. The framework is exemplified through a case study of a popular Danish digital mathematics platform. In a concluding discussion, the paper considers the importance of addressing unsettled and ethical questions about the role of automated digital systems in teachers' knowledge practices.
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- 2024
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136. Traffic Sign Detection with Convolutional Neural Networks
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Peng, Evan, Chen, Feng, Song, Xinkai, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Sun, Fuchun, editor, Liu, Huaping, editor, and Hu, Dewen, editor
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- 2017
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137. Automatic Compound Figure Separation in Scientific Articles: A Study of Edge Map and Its Role for Stitched Panel Boundary Detection
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Aafaque, A., Santosh, K. C., Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Santosh, K.C., editor, Hangarge, Mallikarjun, editor, Bevilacqua, Vitoantonio, editor, and Negi, Atul, editor
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- 2017
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138. The Relationship Between Workload and Performance in Air Traffic Control: Exploring the Influence of Levels of Automation and Variation in Task Demand
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Edwards, Tamsyn, Martin, Lynne, Bienert, Nancy, Mercer, Joey, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Longo, Luca, editor, and Leva, M. Chiara, editor
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- 2017
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139. Characterization of wax valving and μPIV analysis of microscale flow in paper-fluidic devices for improved modeling and design
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Emilie I. Newsham, Elizabeth A. Phillips, Hui Ma, Megan M. Chang, Steven T. Wereley, and Jacqueline C. Linnes
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Automation ,Microfluidics ,Biomedical Engineering ,Bioengineering ,General Chemistry ,Microfluidic Analytical Techniques ,Rheology ,Biochemistry ,Nucleic Acid Amplification Techniques - Abstract
Paper-fluidic devices are a popular platform for point-of-care diagnostics due to their low cost, ease of use, and equipment-free detection of target molecules. They are limited, however, by their lack of sensitivity and inability to incorporate more complex processes, such as nucleic acid amplification or enzymatic signal enhancement. To address these limitations, various valves have previously been implemented in paper-fluidic devices to control fluid obstruction and release. However, incorporation of valves into new devices is a highly iterative, time-intensive process due to limited experimental data describing the microscale flow that drives the biophysical reactions in the assay. In this paper, we tested and modeled different geometries of thermally actuated valves to investigate how they can be more easily implemented in an LFIA with precise control of actuation time, flow rate, and flow pattern. We demonstrate that bulk flow measurements alone cannot estimate the highly variable microscale properties and effects on LFIA signal development. To further quantify the microfluidic properties of paper-fluidic devices, micro-particle image velocimetry was used to quantify fluorescent nanoparticle flow through the membranes and demonstrated divergent properties from bulk flow that may explain additional variability in LFIA signal generation. Altogether, we demonstrate that a more robust characterization of paper-fluidic devices can permit fine-tuning of parameters for precise automation of multi-step assays and inform analytical models for more efficient design.
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- 2023
140. Creation of new textile utilizing Nishijin's hikibaku technique and exploring new applications in other industries.
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Kano, Masashi and Kuwahara, Noriaki
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TEXTILES ,PAPER arts ,TECHNICAL textiles ,LEATHER ,WEAVING - Abstract
Nishijin is famous for its traditional technique of cutting Japanese paper to a thickness of 0.2 to 0.3 mm and weaving it with warp and weft threads. This technique is called ' hikibaku '. In the previous paper, we reported on the creation of a new textile with a new tactile feeling by using natural cowhide instead of Japanese paper used in hikibaku. In this paper, we describe the details of the automation of the hikibaku technique that created the new textile, and conduct a durability test of the newly produced textile using artificial leather, which is of stable quality, instead of natural cowhide, and discuss its new applications. [ABSTRACT FROM AUTHOR]
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- 2023
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141. Enhancing supply chain agility through information systems artifacts and process standardization: an empirical assessment
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Saeed, Khawaja, Malhotra, Manoj, and Abdinnour, Sue
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- 2024
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142. Authoring Conversational Intelligent Tutoring Systems
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Cai, Zhiqiang, Hu, Xiangen, and Graesser, Arthur C.
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Conversational Intelligent Tutoring Systems (ITSs) are expensive to develop. While simple online courseware could be easily authored by teachers, the authoring of conversational ITSs usually involves a team of experts with different expertise, including domain experts, linguists, instruction designers, programmers, artists, computer scientists, etc. Reducing the authoring cost has long been a problem in the use of ITSs. Using AutoTutor as example, this paper discusses the authoring process and possible solutions by automatizing some authoring processes in authoring conversational ITSs. [This paper was published in: "HCII 2019, LNCS 11597," edited by R. A. Sottilare and J. Schwarz, Springer Nature Switzerland AG, 2019, pp. 593-603.]
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- 2019
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143. An Approach to Automatic Reconstruction of Apictorial Hand Torn Paper Document.
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Lotus, Rayappan, Varghese, Justin, and Saudia, Subash
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AUTOMATION ,PAPER ,ARCHAEOLOGY ,FORENSIC sciences ,ALGORITHMS - Abstract
Digital automation in reconstruction of apictorial hand torn paper document increases efficacy and reduces human effort. Reconstruction of torn document has importance in various fields like archaeology, art conservation and forensic sciences. The devised novel technique for hand torn paper document, consists of pre-processing, feature extraction and reconstruction phase. Torn fragment's boundaries are simplified as polygons using douglas peucker polyline simplification algorithm. Features such as Euclidean distance and number of sudden changes in contour orientation are extracted. Our matching criteria identify the matching counterparts. Proposed features curtail ambiguity and enriches efficacy in reconstruction. Reconstructed results of hand torn paper document favour the proposed methodology. [ABSTRACT FROM AUTHOR]
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- 2016
144. An Examination of Automatic Speech Recognition (ASR)-Based Computer-assisted Pronunciation Training (CAPT) for Less-Proficient EFL Students Using the Technology Acceptance Model
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Hsiao-Wen Hsu
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The implementation of computer-assisted pronunciation training (CAPT) has been proven to be successful in improving learners' pronunciation abilities. Automatic speech recognition (ASR) software was used to provide mediated support to 103 pre-intermediate level students (62 males and 41 females). After experiencing a two-semester of CAPT instruction in their Freshman English course, students completed a questionnaire to assess their perceptions of and attitudes towards technology. This paper reports on the findings that examine the structural relationships using the Technology Acceptance Model (TAM). The findings indicate that students, generally, were in favor of using ASR-based pronunciation training, and although no statistically significant gender difference was found, female students appeared to view its use more favorably than were their male counterparts. The perceived effectiveness of the system, and the attitudes of students towards using it, were shown to be significantly correlated, which encourages the ongoing use of ASR-based CAPT. Based on these responses, it was established that the ASR function enhanced students' awareness of their pronunciation errors. Furthermore, they willingly engaged in individual, repetitive pronunciation exercises, allowing them to build confidence in speaking practices without fearing embarrassment in front of their peers. Recommendations were provided for EFL educators interested in implementing CAPT in EFL settings.
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- 2024
145. Promoting Socioeconomic Equity through Automatic Formative Assessment
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Alice Barana and Marina Marchisio Conte
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Ensuring equity in education is a goal for sustainable development. Among the factors that hinder equity, socioeconomic status (SES) has the highest impact on learning Mathematics. This paper addresses the issue of equity at the secondary school level by proposing an approach based on adopting automatic formative assessment (AFA). Carefully designed mathematical activities with interactive feedback were experimented with a sample of 299 students of grade 8 for a school year. A control group of 257 students learned the same topics using traditional methodologies. Part of the sample belonged to low SES. The learning achievement was assessed through pre-and post-tests to understand if the adoption of AFA impacted learning and whether the results depended on the students' SES. The results show a positive effect of the experimentation (effect size: 0.42). Moreover, the effect size of the experimentation restricted to the low-SES group is high (0.77). In the treatment group, the results do not depend on SES, while in the control group, they do, suggesting that AFA is an equitable approach while traditional instruction risks perpetuating inequalities.
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- 2024
146. Robo Academic Advisor: Can Chatbots and Artificial Intelligence Replace Human Interaction?
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Mohammed Muneerali Thottoli, Badria Hamed Alruqaishi, and Arockiasamy Soosaimanickam
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Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature on chatbots and AI in light of their role in auto-advising systems. The authors aimed to gain insights into the most pertinent topics and concerns related to robo academic advisor and identify any gaps in the literature that could serve as potential avenues for further research. Design/methodology/approach: The research employs a systematic literature review and bibliometric techniques to find 67 primary papers that have been published between 1984 and 2023. Using the Scopus database, the researchers built a summary of the literature on chatbots and AI in academic advice. Findings: Chatbot applications can be a promising approach to address the challenges of balancing personalized student advising with automation. More empirical research is required, especially on chatbots and other AI-based advising systems, to understand their effectiveness and how they can be integrated into educational settings. Research limitations/implications: This research's sample size may restrict its findings' generalizability. Furthermore, the study's focus on chatbots may overlook the potential benefits of other AI technologies in enhancing robo academic advising systems. Future research could explore the impact of robo academic advisors in diverse societal backgrounds to gain a more comprehensive understanding of their implications. Practical implications: Higher educational institutions (HEIs) should establish a robo academic advising system that serves various stakeholders. The system's chatbots and AI features must be user-friendly, considering the customers' familiarity with robots. Originality/value: This study contributes to a better understanding of HEIs' perceptions of the adoption of chatbots and AI in academic advising by providing insightful information about the main forces behind robo academic advising, illuminating the most frequently studied uses of chatbots and AI in academic advising.
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- 2024
147. Artificial Intelligence and Automation in the Migration Governance of International Students: An Accidental Ethnography
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Lisa Ruth Brunner and Wei William Tao
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Artificial intelligence (AI) and automation are newly impacting the governance of international students, a temporary resident category significant for both direct economic contributions and the formation of a "pool" of potential future immigrants in many immigrant-dependent countries. This paper focuses on tensions within Canada's education-migration ("edugration") system as new technologies intersect with migration regimes, which in turn relate to broader issues of security, administrative burdens, migration governance, and border imperialism. Using an Accidental Ethnography (AccE) approach drawing from practitioner-based legal research, we discuss three themes: (1) "bots at the gate" and the guise of AI's objectivity; (2) a murky international edu-tech industry; and (3) the administrative burdens of digitalized application systems. We suggest that researchers, particularly in education, can benefit from the insights of immigration practitioners who often become aware of potential trends before those less embedded in the everyday negotiation of migration governance.
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- 2024
148. Improving Teachers' Questioning Quality through Automated Feedback: A Mixed-Methods Randomized Controlled Trial in Brick-and-Mortar Classrooms. EdWorkingPaper No. 23-875
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Annenberg Institute for School Reform at Brown University, Dorottya Demszky, Jing Liu, Heather C. Hill, Shyamoli Sanghi, and Ariel Chung
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While recent studies have demonstrated the potential of automated feedback to enhance teacher instruction in virtual settings, its efficacy in traditional classrooms remains unexplored. In collaboration with TeachFX, we conducted a pre-registered randomized controlled trial involving 523 Utah mathematics and science teachers to assess the impact of automated feedback in K-12 classrooms. This feedback targeted "focusing questions" -- questions that probe students' thinking by pressing for explanations and reflection. Our findings indicate that automated feedback increased teachers' use of focusing questions by 20%. However, there was no discernible effect on other teaching practices. Qualitative interviews revealed mixed engagement with the automated feedback: some teachers noticed and appreciated the reflective insights from the feedback, while others had no knowledge of it. Teachers also expressed skepticism about the accuracy of feedback, concerns about data security, and/or noted that time constraints prevented their engagement with the feedback. Our findings highlight avenues for future work, including integrating this feedback into existing professional development activities to maximize its effect. [This paper was written with TeachFX and financial support was provided from the Learning Agency.]
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- 2023
149. Generative Grading: Near Human-Level Accuracy for Automated Feedback on Richly Structured Problems
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Malik, Ali, Wu, Mike, Vasavada, Vrinda, Song, Jinpeng, Coots, Madison, Mitchell, John, Goodman, Noah, and Piech, Chris
- Abstract
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until recently, achieving anything near human-level accuracy has been unattainable. In this paper, we present generative grading: a novel computational approach for providing feedback at scale that is capable of accurately grading student work and providing nuanced, interpretable feedback. Our approach uses generative descriptions of student cognition, written as probabilistic programs, to synthesise millions of labelled example solutions to a problem; we then learn to infer feedback for real student solutions based on this cognitive model. We apply our methods to three settings. In block-based coding, we achieve a 50% improvement upon the previous best results for feedback, exceeding human-level accuracy. In two other widely different domains--graphical tasks and short text answers--we achieve improvements over the previous state of the art by about 4x and 1.5x respectively, approaching human accuracy. In a real classroom, we ran an experiment with our system to augment human graders, yielding doubled grading accuracy while halving grading time. [For the full proceedings, see ED615472.]
- Published
- 2021
150. Method for automating the processes of generating and using 4D BIM models integrated with location-based planning and Last Planner® System
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Silveira, Bruno Falcón and Costa, Dayana Bastos
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- 2024
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