Relevant bibliographies by topics / Learning artifact

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Learning artifact'

Author: Grafiati
Published: 25 June 2021
Last updated: 17 February 2022

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Journal articles on the topic "Learning artifact"

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Fahrenbach, Florian, Kate Revoredo, and Flavia Maria Santoro. "Valuing prior learning." European Journal of Training and Development 44, no. 2/3 (2019): 209–35. http://dx.doi.org/10.1108/ejtd-05-2019-0070.

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Purpose This paper aims to introduce an information and communication technology (ICT) artifact that uses text mining to support the innovative and standardized assessment of professional competences within the validation of prior learning (VPL). Assessment means comparing identified and documented professional competences against a standard or reference point. The designed artifact is evaluated by matching a set of curriculum vitae (CV) scraped from LinkedIn against a comprehensive model of professional competence. Design/methodology/approach A design science approach informed the development and evaluation of the ICT artifact presented in this paper. Findings A proof of concept shows that the ICT artifact can support assessors within the validation of prior learning procedure. Rather the output of such an ICT artifact can be used to structure documentation in the validation process. Research limitations/implications Evaluating the artifact shows that ICT support to assess documented learning outcomes is a promising endeavor but remains a challenge. Further research should work on standardized ways to document professional competences, ICT artifacts capture the semantic content of documents, and refine ontologies of theoretical models of professional competences. Practical implications Text mining methods to assess professional competences rely on large bodies of textual data, and thus a thoroughly built and large portfolio is necessary as input for this ICT artifact. Originality/value Following the recent call of European policymakers to develop standardized and ICT-based approaches for the assessment of professional competences, an ICT artifact that supports the automatized assessment of professional competences within the validation of prior learning is designed and evaluated.
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Kromrey, M. L., D. Tamada, H. Johno, et al. "Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning–based filter using convolutional neural network." European Radiology 30, no. 11 (2020): 5923–32. http://dx.doi.org/10.1007/s00330-020-07006-1.

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Abstract Objectives To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium–enhanced multi-arterial phase MRI of the liver. Methods This retrospective study included 192 patients (131 men, 68.7 ± 10.3 years) receiving gadoxetate disodium–enhanced liver MRI in 2017. Datasets were submitted to a newly developed filter (MARC), consisting of 7 convolutional layers, and trained on 14,190 cropped images generated from abdominal MR images. Motion artifact for training was simulated by adding periodic k-space domain noise to the images. Original and filtered images of pre-contrast and 6 arterial phases (7 image sets per patient resulting in 1344 sets in total) were evaluated regarding motion artifacts on a 4-point scale. Lesion conspicuity in original and filtered images was ranked by side-by-side comparison. Results Of the 1344 original image sets, motion artifact score was 2 in 597, 3 in 165, and 4 in 54 sets. MARC significantly improved image quality over all phases showing an average motion artifact score of 1.97 ± 0.72 compared to 2.53 ± 0.71 in original MR images (p < 0.001). MARC improved motion scores from 2 to 1 in 177/596 (29.65%), from 3 to 2 in 119/165 (72.12%), and from 4 to 3 in 34/54 sets (62.96%). Lesion conspicuity was significantly improved (p < 0.001) without removing anatomical details. Conclusions Motion artifacts and lesion conspicuity of gadoxetate disodium–enhanced arterial phase liver MRI were significantly improved by the MARC filter, especially in cases with substantial artifacts. This method can be of high clinical value in subjects with failing breath-hold in the scan. Key Points • This study presents a newly developed deep learning–based filter for artifact reduction using convolutional neural network (motion artifact reduction with convolutional neural network, MARC). • MARC significantly improved MR image quality after gadoxetate disodium administration by reducing motion artifacts, especially in cases with severely degraded images. • Postprocessing with MARC led to better lesion conspicuity without removing anatomical details.
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Hasasneh, Ahmad, Nikolas Kampel, Praveen Sripad, N. Jon Shah, and Jürgen Dammers. "Deep Learning Approach for Automatic Classification of Ocular and Cardiac Artifacts in MEG Data." Journal of Engineering 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/1350692.

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We propose an artifact classification scheme based on a combined deep and convolutional neural network (DCNN) model, to automatically identify cardiac and ocular artifacts from neuromagnetic data, without the need for additional electrocardiogram (ECG) and electrooculogram (EOG) recordings. From independent components, the model uses both the spatial and temporal information of the decomposed magnetoencephalography (MEG) data. In total, 7122 samples were used after data augmentation, in which task and nontask related MEG recordings from 48 subjects served as the database for this study. Artifact rejection was applied using the combined model, which achieved a sensitivity and specificity of 91.8% and 97.4%, respectively. The overall accuracy of the model was validated using a cross-validation test and revealed a median accuracy of 94.4%, indicating high reliability of the DCNN-based artifact removal in task and nontask related MEG experiments. The major advantages of the proposed method are as follows: (1) it is a fully automated and user independent workflow of artifact classification in MEG data; (2) once the model is trained there is no need for auxiliary signal recordings; (3) the flexibility in the model design and training allows for various modalities (MEG/EEG) and various sensor types.
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Deepika, J., T. Senthil, C. Rajan, and A. Surendar. "Machine learning algorithms: a background artifact." International Journal of Engineering & Technology 7, no. 1.1 (2017): 143. http://dx.doi.org/10.14419/ijet.v7i1.1.9214.

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With the greater development of technology and automation human history is predominantly updated. The technology movement shifted from large mainframes to PCs to cloud when computing the available data for a larger period. This has happened only due to the advent of many tools and practices, that elevated the next generation in computing. A large number of techniques has been developed so far to automate such computing. Research dragged towards training the computers to behave similar to human intelligence. Here the diversity of machine learning came into play for knowledge discovery. Machine Learning (ML) is applied in many areas such as medical, marketing, telecommunications, and stock, health care and so on. This paper presents reviews about machine learning algorithm foundations, its types and flavors together with R code and Python scripts possibly for each machine learning techniques.
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Graffieti, Gabriele, and Davide Maltoni. "Artifact-Free Single Image Defogging." Atmosphere 12, no. 5 (2021): 577. http://dx.doi.org/10.3390/atmos12050577.

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In this paper, we present a novel defogging technique, named CurL-Defog, with the aim of minimizing the insertion of artifacts while maintaining good contrast restoration and visibility enhancement. Many learning-based defogging approaches rely on paired data, where fog is artificially added to clear images; this usually provides good results on mildly fogged images but is not effective for difficult cases. On the other hand, the models trained with real data can produce visually impressive results, but unwanted artifacts are often present. We propose a curriculum learning strategy and an enhanced CycleGAN model to reduce the number of produced artifacts, where both synthetic and real data are used in the training procedure. We also introduce a new metric, called HArD (Hazy Artifact Detector), to numerically quantify the number of artifacts in the defogged images, thus avoiding the tedious and subjective manual inspection of the results. HArD is then combined with other defogging indicators to produce a solid metric that is not deceived by the presence of artifacts. The proposed approach compares favorably with state-of-the-art techniques on both real and synthetic datasets.
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Lee, Seung-Bo, Hakseung Kim, Young-Tak Kim, et al. "Artifact removal from neurophysiological signals: impact on intracranial and arterial pressure monitoring in traumatic brain injury." Journal of Neurosurgery 132, no. 6 (2020): 1952–60. http://dx.doi.org/10.3171/2019.2.jns182260.

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OBJECTIVEMonitoring intracranial and arterial blood pressure (ICP and ABP, respectively) provides crucial information regarding the neurological status of patients with traumatic brain injury (TBI). However, these signals are often heavily affected by artifacts, which may significantly reduce the reliability of the clinical determinations derived from the signals. The goal of this work was to eliminate signal artifacts from continuous ICP and ABP monitoring via deep learning techniques and to assess the changes in the prognostic capacities of clinical parameters after artifact elimination.METHODSThe first 24 hours of monitoring ICP and ABP in a total of 309 patients with TBI was retrospectively analyzed. An artifact elimination model for ICP and ABP was constructed via a stacked convolutional autoencoder (SCAE) and convolutional neural network (CNN) with 10-fold cross-validation tests. The prevalence and prognostic capacity of ICP- and ABP-related clinical events were compared before and after artifact elimination.RESULTSThe proposed SCAE-CNN model exhibited reliable accuracy in eliminating ABP and ICP artifacts (net prediction rates of 97% and 94%, respectively). The prevalence of ICP- and ABP-related clinical events (i.e., systemic hypotension, intracranial hypertension, cerebral hypoperfusion, and poor cerebrovascular reactivity) all decreased significantly after artifact removal.CONCLUSIONSThe SCAE-CNN model can be reliably used to eliminate artifacts, which significantly improves the reliability and efficacy of ICP- and ABP-derived clinical parameters for prognostic determinations after TBI.
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Wu, Chao, Xiaonan Zhao, Mark Welsh, et al. "Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing." Clinical Chemistry 66, no. 1 (2019): 239–46. http://dx.doi.org/10.1373/clinchem.2019.308213.

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Abstract BACKGROUND Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories rely on manual screening, which is costly, subjective, and not scalable. We present a machine learning–based method to distinguish artifacts from bona fide single-nucleotide variants (SNVs) detected by next-generation sequencing from nonformalin-fixed paraffin-embedded tumor specimens. METHODS A cohort of 11278 SNVs identified through clinical sequencing of tumor specimens was collected and divided into training, validation, and test sets. Each SNV was manually inspected and labeled as either real or artifact as part of clinical laboratory workflow. A 3-class (real, artifact, and uncertain) model was developed on the training set, fine-tuned with the validation set, and then evaluated on the test set. Prediction intervals reflecting the certainty of the classifications were derived during the process to label “uncertain” variants. RESULTS The optimized classifier demonstrated 100% specificity and 97% sensitivity over 5587 SNVs of the test set. Overall, 1252 of 1341 true-positive variants were identified as real, 4143 of 4246 false-positive calls were deemed artifacts, whereas only 192 (3.4%) SNVs were labeled as “uncertain,” with zero misclassification between the true positives and artifacts in the test set. CONCLUSIONS We presented a computational classifier to identify variant artifacts detected from tumor sequencing. Overall, 96.6% of the SNVs received definitive labels and thus were exempt from manual review. This framework could improve quality and efficiency of the variant review process in clinical laboratories.
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Weiss, Dennis M. "Learning to be human with sociable robots." Paladyn, Journal of Behavioral Robotics 11, no. 1 (2020): 19–30. http://dx.doi.org/10.1515/pjbr-2020-0002.

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AbstractThis essay examines the debate over the status of sociable robots and relational artifacts through the prism of our relationship to television. In their work on human-technology relations, Cynthia Breazeal and Sherry Turkle have staked out starkly different assessments. Breazeal’s work on sociable robots suggests that these technological artifacts will be human helpmates and sociable companions. Sherry Turkle argues that such relational artifacts seduce us into simulated relationships with technological others that largely serve to exploit our emotional vulnerabilities and undermine authentic human relationships. Drawing on an analysis of the television as our first relational artifact and on the AMC television show Humans, this essay argues that in order to intervene in this debate we need a multimediated theory of technology that situates our technical artifacts in the domestic realm and examines their impact on those populations especially impacted by such technologies, including women, children, and the elderly. It is only then that we will be able to take the full measure of the impact of such sociable technologies on our being human.
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Bedi, Pradeep, S. B. Goyal, Dileep Kumar Yadav, Sunil Kumar, and Monika Sharma. "Hybrid Learning Model for Metal Artifact Reduction." Journal of Physics: Conference Series 1714 (January 2021): 012021. http://dx.doi.org/10.1088/1742-6596/1714/1/012021.

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Parmaxi, Antigoni, and Panayiotis Zaphiris. "Emerging Technologies for Artifact Construction in Learning." Computers in Human Behavior 99 (October 2019): 366–67. http://dx.doi.org/10.1016/j.chb.2019.05.034.

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Dissertations / Theses on the topic "Learning artifact"

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Eireflet, Johan, and Buhtoo Helen Petersson. "Det nya verktyget : En undersökning av förskollärares upplevelser med surfplattan." Thesis, Högskolan i Halmstad, Akademin för lärande, humaniora och samhälle, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-28141.

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The aim of this thesis is to study preschool-teachers’ experiences from using the computer tablet as a tool for learning and teaching, in order to gain knowledge of how the integrational process of information and communications technology (ICT) in preschool has progressed since its instatement. The background that caused interest to make this study was the rapid progression of the use of ICT-tools in childrens’ everyday lives and the troubles that have surrounded the process of integrating these tools into preschool-practices. The theoretical basis for the analysis of the research lies within the socio-cultural perspective. The methods used to gather empirical data were discussions held in focus-groups consisting of teachers from three different preschools in Sweden where the theme of the discussions were computer tablets. In accordance with a socio-cultural approach to verbal communication as data the discussions were seen as socially situated practices. The results of this study were that tablets were only in part integrated with school-activities as they were well used for by the pedagogues for purposes such as organizing, documentation and communication but not as well used among the children due to different circumstances. Another finding of the study was that teachers find that they often lack the ICT-competences required to develop good learning situations and conditions for their students with the computer tablets. Based on the teachers’ testimonies not only is there a need for in-service training for teachers but perhaps also necessary to provide teachers with further direction for work with computer tablets, how they should be used and the extent of their role within preschool settings.
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Dumas, Kuchling Janine. "1:1 Digital devices and preparatory school teachers’ classroom practices." Diss., University of Pretoria, 2020. http://hdl.handle.net/2263/80435.

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In this study, the influence of a 1:1 digital device on South African preparatory school teachers’ perceptions regarding their classroom practices is described. The focus is on the Chromebook as an ‘artifact’ of learning. Digital technology is becoming prevalent in all education spheres and, subsequently, interest in this topic is growing. In order to create an environment where optimal learning takes place, teachers and pupils should adapt their learning and teaching methods to embrace the effects of technology. Teachers are at the forefront of education and education trends involving digital devices are becoming a reality across all grades. Qualitative research was conducted to gain insight into eight teachers’ perceptions on using a 1:1 digital device (the Chromebook) for teaching and learning in a private Gauteng school. The major findings were that teachers had to adapt their preparation, facilitation and assessment strategies to accommodate the use of the Chromebook in the classroom. This was mostly done successfully by the participants. The teachers realised that the Chromebook is a useful learning and teaching artifact or learning and teaching support material as a tool in the classroom. It enhances multimodal learning, encourages the inclusion of multiliteracies, and creates a third space of learning, where teachers and pupils cooperate in constructing new knowledge. A concern addressed by the teachers was that digital learning would have a negative impact on writing skills. They also stated that there should be a balance between technology and traditional teaching methods. The most important recommendations are that teachers should change their attitude and their preparation and implementation of lessons when using the digital device in the classroom. Teachers should realise that pupils whose parents have the financial means and who have access to trending technology, today’s digital natives, have instant access to information and this has changed the way learning takes place. Although new to some teachers, the use of digital devices is second nature for many pupils of the 21st century. Teachers should embrace opportunities for professional development so that the digital device can be effectively incorporated in the learning process in the classroom.<br>Dissertation (MEd)--University of Pretoria 2020.<br>pt2021<br>Humanities Education<br>MEd<br>Unrestricted
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Riblett, Matthew J. "Motion-Induced Artifact Mitigation and Image Enhancement Strategies for Four-Dimensional Fan-Beam and Cone-Beam Computed Tomography." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5542.

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Four dimensional imaging has become part of the standard of care for diagnosing and treating non-small cell lung cancer. In radiotherapy applications 4D fan-beam computed tomography (4D-CT) and 4D cone-beam computed tomography (4D-CBCT) are two advanced imaging modalities that afford clinical practitioners knowledge of the underlying kinematics and structural dynamics of diseased tissues and provide insight into the effects of regular organ motion and the nature of tissue deformation over time. While these imaging techniques can facilitate the use of more targeted radiotherapies, issues surrounding image quality and accuracy currently limit the utility of these images clinically. The purpose of this project is to develop methods that retrospectively compensate for anatomical motion in 4D-CBCT and correct motion artifacts present in 4D-CT to improve the image quality of reconstructed volume and assist in localizing respiration-influenced, diseased tissue and mobile structures of interest. In the first half of the project, a series of motion compensation (MoCo) workflow methods incorporating groupwise deformable image registration and projection-warped reconstruction were developed for use with 4D-CBCT imaging. In the latter half of the project, novel motion artifact observation and artifact- weighted groupwise registration-based image correction algorithms were designed and tested. Both deliverable components of this project were evaluated for their ability to enhance image quality when applied to clinical patient datasets and demonstrated qualitative and quantitative improvements over current state-of-the-art.
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Gibbs, Béatrice. "Wii lär oss dansa? : Om dansspel, rörelsekvaliteter och lärande i idrott och hälsa." Licentiate thesis, Gymnastik- och idrottshögskolan, GIH, Forskningsgruppen för pedagogik, idrott och fritidskultur, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-3345.

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Few studies have focused on how learning takes place in physical education and health (PEH) practices, and even more so in relation to artifact use. Dance is a core content in the Swedish curriculum, but according to previous research it nevertheless rarely occurs in practice due to many teachers’ lack of knowledge. Movement qualities are something that students are supposed to develop in the subject, where dance can be used as a form of activity. The aim of the licentiate thesis is to examine students’ use and development of different movement qualities in a learning process where dance exergames are used as teaching aids in the PEH practice in upper secondary school. The research questions in the study are: (1) what kind of movement qualities do students use when they interact with each other and with dance exergames, and (2) how does the learning of movement qualities occur when dance exergames are used as teaching aids? A series of seven PEH-lessons were designed. Four of the lesson had a spe-cific purpose, such as working with rhythm and coordination where the exergames Nintendo Wii Just Dance 3 and 4 were used as teaching aids. In two other lessons the students worked in groups to create their own dances, and as a final goal, at lesson seven, the groups presented their dances. All the lessons were video recorded. A framework inspired by Laban’s movement analysis was used to analyze the students’ movement qualities, based on four aspects: body, space, effort and relationship. To be able to analyze the students, the dance exergames and the context as a whole, the study involved a socio-cultural ap-proach to learning. Learning situations in the ongoing practice were also ana-lyzed, where learning was investigated as something that occurs through inter-actions between students and between students and artifacts. The results show a way to describe students’ movement qualities, which con-tribute to PEH-teachers language of knowledge in movement. The results also demonstrate that learning occurred through imitation, repetition, communica-tion, negotiation, practice, modeling, instruction and using metaphors. A con-clusion is that students’ use and development of movement qualities do not depend on the use of the dance exergames per se, instead it depends on how the dance exergames are used in PEH practice.<br>Forskningslinjen Utbildning
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Thorén, Mia. ""Och väggarna förvandlades till världen runtomkring" : pedagogers röster och praktiker kring att främja elevers fantasi och kreativitet i och genom fritidshemmets inomhusmiljö." Thesis, Högskolan Kristianstad, Fakulteten för lärarutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hkr:diva-20270.

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Betoningen i fritidshemmets och dess pedagogers uppdrag ligger på det som många gånger är oförutsägbart – lek, utforskande och kreativa arbetssätt samt att främja elevers fantasi och kreativitet. Fritidshemmet är även en fysisk plats – en komplex miljö där förväntningar om informellt lärande och omsorg ska iscensättas och ta plats. Den fysiska inomhusmiljön i fritidshemmet och pedagogernas roll i att använda den som en del av det pedagogiska uppdraget finns inte i detalj specificerat i styrdokumenten och är ett område som inte tidigare prioriterats högt i akademisk forskning, men kan ses vara på tydlig uppgång. Studien, som genomförts i form av samtalspromenader tillsammans med pedagoger på fyra fritidshem i Skåne syftar till att – genom ett designteoretiskt och sociokulturellt perspektiv – belysa pedagogers intentioner och praktiker kring att främja elevers kreativitet och fantasi i och genom den fysiska inomhusmiljön på fritidshemmet. Den ställer även frågan kring vilka artefakter som används för detta syfte och på vilket sätt de presenteras för eleverna. Studiens resultat visar en samstämmig bild av både det utbud av artefakter som presenteras för elever i syfte att främja kreativitet och fantasi, och ett ospecificerat uppdrag som i högsta grad är levande för pedagogerna men många gånger är marginaliserat.<br>The emphasis of Swedish leisure-time teachers assignment lies in the unpredictable characteristics of play, explorative and creative ways of working and encouraging child fantasy and creativity. The leisure time centre is also a physical space where a complex mix of expectations of informal learning and care takes place.   The physical learning environment of Swedish leisure-time centres, and the teacher’s assignment concerning it, is neither in detail regulated in steering documents nor well documented in academic research but seems to be an upcoming subject of attention.   This study, which has been executed as walking interviews with teachers in four Swedish leisure-time centres, aims to – through a sociocultural and multimodal theoretical perspective – illustrate the intention and applied practices concerning the encouraging of child fantasy and creativity in and through physical learning environment. It also aims to explore the use and range of artifacts and how they are presented to children.   The results of this study present a unanimous picture of the range of artifacts used and an assignment highly vivid to the teachers but still unspecified as well as marginalized.
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Ghazi, Shabo Andira, and Amal Audish Basa Sarok. "Vilka beskrivningar avteknikämnet framkommer hosniondeklassare i grundskolan?" Thesis, KTH, Lärande, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280878.

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Syftet med denna studie har varit att förstå hur högstadieelever i årskurs 9 i sex svenska skolor beskriver teknikämnet samt ta reda på vad de uppger att det de har lärt sig respektive vad de saknat kring innehåll i teknikämnet efter 9 år i grundskolan. Studien bygger på en enkätundersökning ifylld med hjälp av papper och penna. Respondenter fick svara på frågorkring vad de anser att teknik är, samt vad de har lärt sig och eventuellt saknat iteknikundervisningen under grundskolans gång. 252 enkäter delades ut och 250 besvarades. DiGirnonimos (2011) ramverk har använts för att kategorisera uttalanden avseende teknikens natur som framkommer i elevernas enkätsvar. I resultatet framkommer att teknik beskrivet som artefakt och teknik som skapandeprocess samt beskrivningar relaterade till teknikens roll i samhället är de mest återkommande dimensionerna i respondenternas svar. Däremot är det inte så många elever som beskriver teknik relaterat till teknikens historia eller teknik som mänsklig verksamhet. Ett annat innehåll som framhålls av eleverna som något de har lärt sig mycket om är programmering. Teman såsom el-teknik, sätt att tänka för att lösa problem etc.(som en ingenjör), tekniska system, miljöfrågor relaterat till teknik framkommer också, dock med avsevärt mindre frekvens. Resultatet visar att eleverna generellt nämner innehållet i teknikundervisning från olika håll, Många elever kan uttrycka flera av DiGironimosdimensioner när de får frågan om vad teknik är. Men eftersom vissa områden, exempelvis denhistoriska dimensionen inte riktigt framkommer krävs fortfarande tydlighet och en mer välplanerad teknikundervisning för att täcka hela innehållet som står i kursplanen för teknikämnet. En relativt stor andel av eleverna visar osäkerhet kring vilket teknikinnehåll som de saknat i sin teknikundervisning. Det kan förstås bero på att de inte vet vad de har att vänta av undervisningen. Det som framkommer i elevernas svar är att de saknar programmering, teknikinnehåll, konstruktion, resurser, praktiskt arbete vilket också sammanfaller med vad de anser att de lärt sig. En tolkning är att dessa områden är elevernas beskrivning av vad teknikämnet omfattar och att det är detta som de också anser sig behöva mer av.<br>The purpose of this study has been to understand how high school students year 9 in six Swedish schools describe the subject of technology and state what they have learned and what they lacked about content in the subject of technology after 9 years in primary school. The study is based on a questionnaire completed using paper and pen. Respondents had to answer questions about what technology is, and what they have learned and possibly missed in technology teaching during primary school. 252 questionnaires were distributed and 250 were answered. DiGirnonimo's (2011) framework has been used to categorize statements regarding the nature of technology that appear in students' questionnaire responses. The results show that technology described as an artifact and technology as a creative process as well as descriptions related to the role of technology in society are the most recurring  dimensions in the respondents' answers. However, not many students describe technology related to the history of technology or technology as human activity. The results show that students seem to have learned the most about construction technology and drawing technology. Another content that is emphasized by the students as something they have learned a lot about is programming. Themes such as electrical engineering, ways of thinking to solve problems, etc. (as an engineer), technical systems, environmental issues related to technology also emerge, but with less frequency. The results show that students generally mention technology teaching from different angles. Many students can express several of DiGironimo's dimensions when asked what technology is. However, as some areas, such as the historical dimension, do not really emerge, clarity and more well-planned technical teaching are still required to cover the entire content of the syllabus for the technical subject. A relatively large proportion of the students show uncertainty about what technology content they lacked in their technology teaching. This may of course be because they do not know what to expect from the teaching. What emerges in the students' answers is that they lack programming, technical content, construction, resources, practical work, which also coincides with what they think they have learned. One interpretation is that these areas are the students'description of what the subject of technology includes and that this is what they also considerneeding more of.
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Bigenho, Christopher William. "Student reflections as artifacts of self-regulatory behaviors for learning: A tale of two courses." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103291/.

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The rapid growth of online and blended learning environments in both higher education and K-12, along with the development of innovative game based, narrative driven, problem-based learning (PBL) systems known as Alternate Reality Games (AltRG), has led to the need to understand student’s abilities to self-regulate their learning behaviors and practices in these novel environments. This study examines student reflections and e-mails related to self-regulatory practices for learning across two different course designs for an Internet-based course in computer applications. Both designs leverage PBL but apply different levels of abstraction related to content and the need to self-regulate. The study looked specifically at how students communicated about learning across these environments, what student communications indicated about student readiness for university online learning and how instructional design and methods of instruction shaped student expressions of learning and self-regulation. The research design follows an ethnographic and case study approach as two designs and four sections are examined. Data was collected from student blog posts, email messages and semi-structured interviews. Atlas.TI was used to code the data using constant comparative analysis. A sequential analysis was applied using an a priori structure for self-regulation and post hoc analysis for emergent codes that resulted in the following categories: distraction, group experience, motivation, emotion, prior experiences, and time. Results indicated qualitative differences between the two designs related to student communications for learning and self-regulation. Findings were reported for both the a priori and post hoc analysis. Additionally, two major findings are reported as emerging themes. These are presented and discussed as The Expectation Gap and Different Designs, Different Outcomes.
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Wetterlund, Simon. "Samiska politikers lärande : Rätten att få vara exkluderad och fortfarande vara inkluderad." Thesis, Uppsala universitet, Institutionen för pedagogik, didaktik och utbildningsstudier, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254563.

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In this essay i present a study on political learning of a minority ethnicity whose political history in the institutional form began in 1993. The ethnicity in question is the Sami’s and in 1993 the Sami Parliament was established. The establishment of the Sami parliament radically changed the preconditions for political work. Sami politics came to be pursued in an organized manner in the form of a public authority and democratically elected units. In these study Sami politician's perceptions of political learning is investigated. Special attention is directed towards individual- as well as organizational and institutional level. The theories used are Vygotsky's sociocultural perspective on learning complemented with a Foucault-inspired discourse analysis. The method used is semi-structured interviews. The results show that learning is essentially perceived to take place on an individual level and that the organizational and institutional level only to some extent supports the individual level of learning
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Steeples, Christine. "Networked learning environments : continuing professional development and the creation and use of multimedia artifacts." Thesis, Lancaster University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418857.

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Sutter, Berthel. "Instruction at heart. Activity-theoretical studies of learning and development in coronary clinical work." Doctoral thesis, Ronneby : Blekinge Institute of Technology, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00185.

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The aim of the thesis is to study the role of instruction in the interconnection of instruction-learning-development. The thesis consists of six empirical papers and a summing-up and perspectivizing introductory paper. Five of the empirical studies concern so called heart conferences, clinical diagnostic meetings, which at the time of my study, 1995-1996, were arranged as telemediated conferences between a sub-team of surgeons and radiologists in a university clinic, and a sub-team of cardiologists and radiologists in a regional hospital. The outcome of the coronary diagnostic work in the heart conferences was patient diagnoses and decided-upon treatment (surgery, balloon dilatation, or conservative treatment). The sixth empirical study, conducted in the autumn 2000, investigates the design and redesign of a central artifact used in the heart conference, ?the angio film,? produced in the angio lab. A recurrent theme in the empirical papers is whether artifacts might be instructive and, if so, in what ways. The introductory paper is a hybrid between an ordinary summing-up paper of the findings in the empirical studies, and a perspectivizing presentation of activity-theoretical approaches to instruction, learning and development, elaborating on three basic aspects (learning as a collaborative phenomenon, the instructiveness of artifacts, and the relation between learning and development on an individual level, but primarily on an activity level). In conclusion, my study outlines an approach to learning based on new perspectives on instruction.<br>Studier av läkares co-coaching av varandra som ett led i deras samarbete rörande kranskärlsdiagnostiskt arbete. Artefaktanvändning, lärande och versamhetsutveckling.
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Books on the topic "Learning artifact"

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Dillenbourg, Pierre, Jeffrey Huang, and Mauro Cherubini, eds. Interactive Artifacts and Furniture Supporting Collaborative Work and Learning. Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-77234-9.

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Dillenbourg, Pierre. Interactive Artifacts and Furniture Supporting Collaborative Work and Learning. Springer Science+Business Media, LLC, 2009.

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Ivarsson, Jonas. Renderings & reasoning: Studying artifacts in human knowing. Acta Universitatis Gothoburgensis, 2004.

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Artifact Case Studies: Interpreting Children's Work and Teachers' Classroom Strategies (Merrill Education Student Enrichment). Prentice Hall, 2003.

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Ormrod, Jeanne Ellis. Artifact Case Studies: Interpreting Children's Work and Teachers' Classroom Strategies (Merrill Education Student Enrichment). Prentice Hall, 2003.

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1963-, Nehaniv Chrystopher L., and Dautenhahn Kerstin, eds. Imitation in animals and artifacts. MIT Press, 2002.

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Nehaniv, Chrystopher L., and Kerstin Dautenhahn. Imitation in Animals and Artifacts. MIT Press, 2002.

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Nehaniv, Chrystopher L., and Kerstin Dautenhahn. Imitation in Animals and Artifacts. MIT Press, 2019.

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(Editor), Kerstin Dautenhahn, and Chrystopher L. Nehaniv (Editor), eds. Imitation in Animals and Artifacts (Complex Adaptive Systems). The MIT Press, 2002.

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Dillenbourg, Pierre, Jeffrey Huang, and Mauro Cherubini. Interactive Artifacts and Furniture Supporting Collaborative Work and Learning. Springer, 2009.

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Book chapters on the topic "Learning artifact"

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Cole, Mike. "Re-covering the Idea of a Tertiary Artifact." In Cultural-Historical Approaches to Studying Learning and Development. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6826-4_20.

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Hadaya, Pierre, Abderrahmane Leshob, and Julien Nicolas de Verteuil. "An Artifact for Learning the TOGAF Architecture Development Method." In Advances in E-Business Engineering for Ubiquitous Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34986-8_31.

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Huang, Yixing, Alexander Preuhs, Günter Lauritsch, Michael Manhart, Xiaolin Huang, and Andreas Maier. "Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior." In Machine Learning for Medical Image Reconstruction. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33843-5_10.

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Kim, Dong Kyu, and Sam Keene. "Fast Automatic Artifact Annotator for EEG Signals Using Deep Learning." In Biomedical Signal Processing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67494-6_7.

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Cunnington, J. P. W., G. R. Norman, J. M. Blake, W. D. Dauphinee, and D. E. Blackmore. "Applying Learning Taxonomies to Test Items: Is a Fact an Artifact?" In Advances in Medical Education. Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-4886-3_40.

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Sawaragi, Tetsuo. "Reproductive Process-Oriented Data Mining from Interactions between Human and Complex Artifact System." In Machine Learning and Data Mining in Pattern Recognition. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48097-8_15.

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Dora, Chinmayee, and Pradyut Kumar Biswal. "An ELM Based Regression Model for ECG Artifact Minimization from Single Channel EEG." In Intelligent Data Engineering and Automated Learning – IDEAL 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03493-1_29.

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Bordiés, Osmel, Andreas Papasalouros, and Yannis Dimitriadis. "Estimating the Gap between Informal Descriptions and Formal Models of Artifact Flows in CSCL." In Open Learning and Teaching in Educational Communities. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11200-8_66.

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Huang, Yixing, Yanye Lu, Oliver Taubmann, Guenter Lauritsch, and Andreas Maier. "Traditional Machine Learning Techniques for Streak Artifact Reduction in Limited Angle Tomography." In Bildverarbeitung für die Medizin 2018. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-56537-7_62.

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Moyes, Andrew, Kun Zhang, Ming Ji, Huiyu Zhou, and Danny Crookes. "Unsupervised Deep Learning for Stain Separation and Artifact Detection in Histopathology Images." In Communications in Computer and Information Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-52791-4_18.

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Conference papers on the topic "Learning artifact"

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Vasiliou, Christina. "Collaborative Learning In An Artifact Ecology." In the 2015 International Conference. ACM Press, 2015. http://dx.doi.org/10.1145/2817721.2820987.

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Nedelcu, Elena, Raluca Portase, Ramona Tolas, Raul Muresan, Mihaela Dinsoreanu, and Rodica Potolea. "Artifact detection in EEG using machine learning." In 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE, 2017. http://dx.doi.org/10.1109/iccp.2017.8116986.

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Niu, Chuang, Mengzhou Li, and Ge Wang. "Multi-window learning for metal artifact reduction." In Developments in X-Ray Tomography XIII, edited by Bert Müller and Ge Wang. SPIE, 2021. http://dx.doi.org/10.1117/12.2596239.

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Molina, Facundo, Pablo Ponzio, Nazareno Aguirre, and Marcelo Frias. "EvoSpex: An Evolutionary Algorithm for Learning Postconditions (artifact)." In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). IEEE, 2021. http://dx.doi.org/10.1109/icse-companion52605.2021.00080.

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Njomou, Aquilas Tchanjou, Alexandra Johanne Bifona Africa, Bram Adams, and Marios Fokaefs. "MSR4ML: Reconstructing Artifact Traceability in Machine Learning Repositories." In 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER). IEEE, 2021. http://dx.doi.org/10.1109/saner50967.2021.00061.

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Prakash, Prakhar, and Sandeep Dutta. "Deep learning-based artifact detection for diagnostic CT images." In Physics of Medical Imaging, edited by Hilde Bosmans, Guang-Hong Chen, and Taly Gilat Schmidt. SPIE, 2019. http://dx.doi.org/10.1117/12.2511766.

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Xu, Shiyu, and Hao Dang. "Deep residual learning enabled metal artifact reduction in CT." In Physics of Medical Imaging, edited by Guang-Hong Chen, Joseph Y. Lo, and Taly Gilat Schmidt. SPIE, 2018. http://dx.doi.org/10.1117/12.2293945.

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Lee, Sangmin S., Kiwon Lee, and Guiyeom Kang. "EEG Artifact Removal by Bayesian Deep Learning & ICA." In 2020 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) in conjunction with the 43rd Annual Conference of the Canadian Medical and Biological Engineering Society. IEEE, 2020. http://dx.doi.org/10.1109/embc44109.2020.9175785.

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Hu, Yueyu, Haichuan Ma, Dong Liu, and Jiaying Liu. "Compression Artifact Removal with Ensemble Learning of Neural Networks." In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2020. http://dx.doi.org/10.1109/cvprw50498.2020.00074.

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Erkens, Melanie, Oliver Daems, and H. Ulrich Hoppe. "Artifact Analysis around Video Creation in Collaborative STEM Learning Scenarios." In 2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2014. http://dx.doi.org/10.1109/icalt.2014.116.

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Reports on the topic "Learning artifact"

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Chang, Chihway, Alex Drlica-Wagner, Brian Nord, Donah, Michelle Wang, and Michael H. L. S. Wang. A Machine Learning Approach to the Detection of Ghosting Artifacts in Dark Energy Survey Images. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1594126.

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