Relevant bibliographies by topics / Perception and learning

Contents

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

Academic literature on the topic 'Perception and learning'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Perception and learning"

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Lu, Yu-Ling, and Chi-Jui Lien. "Are They Learning or Playing? Students’ Perception Traits and Their Learning Self-Efficacy in a Game-Based Learning Environment." Journal of Educational Computing Research 57, no. 8 (January 21, 2019): 1879–909. http://dx.doi.org/10.1177/0735633118820684.

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As game-based learning continues to draw attention, students’ perceptions toward classroom activities are vital in influencing the quality of learning. This study used the social cognitive theory to show the perception traits of learning and playing in game-based environments and for students to identify their self-efficacy toward game-based learning by different trait groups. The game Formosa Hope was used in an experiment with 362 fifth- and sixth-grade students at ages 11 to 12 years as participants. Three perception traits were identified through a two-step cluster analysis: I—strong perceptions of learning and playing, II—moderate perceptions of learning and playing, and III—strong perception of playing but weak perception of learning. This study showed that regardless of trait type, students demonstrated positive self-efficacy, with those with Trait I having significantly higher self-efficacy than those with Traits II and III, indicating that students’ positive perceptions of learning and playing are essential in prompting self-efficacy in game-based learning.
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Suson, Roberto, Eugenio A. Ermac, Wilfredo G. Anoos, Marjorie B. Anero, Nino Jess D. Tomabiao, Ireneo M. Taperla Jr, Larry C. Gantalao, et al. "Prototype learning activities." Cypriot Journal of Educational Sciences 15, no. 6 (December 31, 2020): 1535–43. http://dx.doi.org/10.18844/cjes.v15i6.5296.

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The study of prototype learning activity has received significant attention to elevating students’ academic performance. This study utilized the prototype learning design as a significant predictor of students’ performance and the like. In addition, this study aimed to explore teachers’ strategies for measuring students’ creative growth utilizing authentic assessments. Moreover, this study used a survey to assess the perception of the students and teachers. The study used the quantitative inferential which provides the relationship between the two variables' effectiveness and perception of the prototype learning activities. The main instrument used to ascertain these parameters are the two survey questionnaires was researcher-made align with the Department of Education Science competency, the reliability and consistency were validated by the statistician. Results revealed that students’ performance was at a high level when engaged in the prototype learning activity. Furthermore, the perception of the students and teachers in terms of ease of use, relevance, and comprehensibility indicates positive perception in relation to the student's performance. Finally, the prototype-based learning approach shows a promising effect on the performance of the student's and teachers' perceptions. Hence, enhancement training in developing a teacher’s capacity to design meaningful learning that caters students' needs should be provided. Keywords: Prototype learning; performance; academic achievement
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Kharisma, Irma, and Liza Andhani Hidayati. "STUDENTS’ PERCEPTION IN LEARNING ENGLISH USING COOPERATIVE LEARNING ACTIVITY." PROJECT (Professional Journal of English Education) 1, no. 3 (June 11, 2018): 207. http://dx.doi.org/10.22460/project.v1i3.p207-216.

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This study aims to know the students’ perceptions about the use of cooperative learning activity in learning English. This study use qualitative research. The sample of this study involved 31 students in class XI social two at SMA Cipta Mandiri in the academic year 2017/2018. In collecting the data the researchers use questionnaire of 20 (twenty) questions that relate to cooperative learning activity. The result of this study shows that most of students agreed if the teacher use cooperative learning activity in the classroom. The students though that through cooperative learning activity, the lesson more interesting and helps them acquire knowledge easily.Keywords: Students’ Perception, Cooperative Learning Actvity
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Sedlmeier, Andreas, and Sebastian Feld. "Learning indoor space perception." Journal of Location Based Services 12, no. 3-4 (October 2, 2018): 179–214. http://dx.doi.org/10.1080/17489725.2018.1539255.

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Watanabe, T., J. E. Nanez, and Y. Sasaki. "Perceptual learning without perception." Journal of Vision 1, no. 3 (March 14, 2010): 467. http://dx.doi.org/10.1167/1.3.467.

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Watanabe, Takeo, José E. Náñez, and Yuka Sasaki. "Perceptual learning without perception." Nature 413, no. 6858 (October 2001): 844–48. http://dx.doi.org/10.1038/35101601.

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Sanga Lamsari Purba, Leony. "Microsoft teams 365 and online learning: The student’s perception." Jurnal Pendidikan Kimia 13, no. 2 (August 1, 2021): 130–36. http://dx.doi.org/10.24114/jpkim.v13i2.26981.

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This study aims to determine the effectiveness of online learning using Microsoft Teams 365. The entire population in this study was used as a research sample, namely all students of the Chemistry Education study program, Indonesian Christian University, Jakarta. Perception data was collected using a questionnaire with dimensions of understanding the material, appearance and accessibility of Microsoft Teams 365. From the results of data processing, it was found that more than 50% of students' perceptions of Microsoft Teams 365 were good in all indicators of understanding the material and appearance. On the use dimension with connectivity and accessibility indicators more than 50% of students' perceptions of the Microsoft 365 team are good, but on the quota-saving indicator 42% of students do not agree. Keywords: Microsoft teams, E-learning, Cemistry
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Suyitno, Imam, Kusubakti Andayani, Peni Dyah Anggari, Taufiq Kurniawan, and Heni Dwi Arista. "FOREIGN LEARNERS’ PERCEPTION, SATISFACTION, AND LEARNING OUTCOME IN LEARNING INDONESIAN LANGUAGE." Jurnal Cakrawala Pendidikan 40, no. 1 (February 15, 2021): 133–46. http://dx.doi.org/10.21831/cp.v40i1.32311.

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Indonesian language learning institute for foreign learners emphasizes on increasing the experiences and skills of foreigners to speak Indonesian in the real context. One of the models used to achieve this is by optimizing the learning process. Therefore, this research studied the learning model and its impact on the perceptions, satisfaction, and outcomes using qualitative and quantitative approaches. The sample study consists of 21 foreign learners and 10 tutors. Data were obtained from the experiential-tutorial learning, scores of perception, satisfaction, and outcomes through interviews, questionnaires, and tutor assessment on the speaking abilities recorded on document sheets. The study found that the experiential-tutorial learning was developed based on the learners’ daily communication needs. The statistical analysis results showed that the average scores of their perception, satisfaction, and learning outcomes were in the high category. Therefore, foreign learners have a good perception and high learning satisfaction in conducting experiential-tutorial learning to increase their outcomes. These findings indicate that experiential-tutorial learning is an effective model for foreign language learners.
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HATANAKA, Wataru, Fumihiro SASAKI, and Ryota YAMASHINA. "Active Perception Policy Learning by Reinforcement Learning." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2020 (2020): 2A1—L02. http://dx.doi.org/10.1299/jsmermd.2020.2a1-l02.

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Anggoro, Bambang Sri. "Analisis Persepsi Siswa SMP terhadap Pembelajaran Matematika ditinjau dari Perbedaan Gender dan Disposisi Berpikir Kreatif Matematis." Al-Jabar : Jurnal Pendidikan Matematika 7, no. 2 (December 20, 2016): 153–66. http://dx.doi.org/10.24042/ajpm.v7i2.30.

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This research is a qualitative research with the qualitative descriptive method. The technique of research subject taking in this research use purposive sampling technique. The subjects of this study amounted to 9 students. Data collection techniques used were questionnaire perception and disposition of students' mathematical creative thinking, observation, interview and documentation of mathematics learning. Data analysis techniques, namely data reduction, data presentation, and conclusions. The validity of data in this study using the content validity, construct validity and reliability and triangulation techniques. According to the results of the study and discussion, the conclusion of this study is Based on the gender and disposition of mathematical creative thinking, the perception of mathematics learning that is produced, that is for high DBKM and positive perception is only found in male students, for high DBKM and medium perception, Male and female students, for medium DBKM and medium perception, female students tend to be more than male students, for medium DBKM and negative perceptions of male students tend to be more than female students, for low DBKM and perception is being Only in boys, and for low DBKM and negative perceptions are only found in female students. The disposition of high mathematical creative thinking and positive perception is very influential on learning mathematics because students who have high DBKM and positive perception will be better in learning mathematics than students who have DBKM and perceptions other than high DBKM and positive perceptions of mathematics learning.
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Dissertations / Theses on the topic "Perception and learning"

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Liu, Chong. "Reinforcement learning with time perception." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/reinforcement-learning-with-time-perception(a03580bd-2dd6-4172-a061-90e8ac3022b8).html.

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Classical value estimation reinforcement learning algorithms do not perform very well in dynamic environments. On the other hand, the reinforcement learning of animals is quite flexible: they can adapt to dynamic environments very quickly and deal with noisy inputs very effectively. One feature that may contribute to animals' good performance in dynamic environments is that they learn and perceive the time to reward. In this research, we attempt to learn and perceive the time to reward and explore situations where the learned time information can be used to improve the performance of the learning agent in dynamic environments. The type of dynamic environments that we are interested in is that type of switching environment which stays the same for a long time, then changes abruptly, and then holds for a long time before another change. The type of dynamics that we mainly focus on is the time to reward, though we also extend the ideas to learning and perceiving other criteria of optimality, e.g. the discounted return, so that they can still work even when the amount of reward may also change. Specifically, both the mean and variance of the time to reward are learned and then used to detect changes in the environment and to decide whether the agent should give up a suboptimal action. When a change in the environment is detected, the learning agent responds specifically to the change in order to recover quickly from it. When it is found that the current action is still worse than the optimal one, the agent gives up this time's exploration of the action and then remakes its decision in order to avoid longer than necessary exploration. The results of our experiments using two real-world problems show that they have effectively sped up learning, reduced the time taken to recover from environmental changes, and improved the performance of the agent after the learning converges in most of the test cases compared with classical value estimation reinforcement learning algorithms. In addition, we have successfully used spiking neurons to implement various phenomena of classical conditioning, the simplest form of animal reinforcement learning in dynamic environments, and also pointed out a possible implementation of instrumental conditioning and general reinforcement learning using similar models.
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Malyan, R. R. "Machine learning for handprinted character perception." Thesis, Kingston University, 1989. http://eprints.kingston.ac.uk/20527/.

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Humans are well suited to the reading of textual information, but unfortunately it has not yet been possible to develop a machine to emulate this form of human behaviour. In the past, machines have been characterised by having static forms of specific knowledge necessary for character recognition. The resulting form of reading behaviour is most uncharacteristic of the way humans perceive textual information. The major problem with handprinted character recognition is the infinite variability in the character shapes and the ambiguities many of these shapes exhibit. Human perception of handprinted characters makes extensive use of "world knowledge" to remove such ambiguities. Humans are also continually modifying their world knowledge to further enhance their reading behaviour by acquiring new knowledge as they read. An information processing model for perception and learning of handprinted characters is proposed. The function of the model is to enable ambiguous character descriptions to converge to single character classifications. The accuracy of this convergence improves with reading experience on handprinted text. The model consists of three compon,ent parts. Firstly, a character classifier to recognise character patterns. These patterns may be both distorted anq noisy, where distortion is defined to be a consistent variability from known archetypical character descriptions and noise as a random inconsistent variability in character shape. Secondly, a perceptive mechanism that makes inferences from an incomplete linguistic world model of an author or of a specific domain of discourse from many authors. Finally, a incremental learning capability is integrated into the character classifier and perceptive mechanisms. This is to enable the internal world model to be continually adaptive to either changes in the domain of discourse or to different authors. A demonstrator is described, together with a summary of experimental results that clearly show the improvement in machine perception which results from continuous incremental learning.
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Öhlander, Andersson Lina. "English Language Learning : Student's Perception on Their Own Language Learning." Thesis, Högskolan i Gävle, Avdelningen för humaniora, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-14371.

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This is a qualitative study, which aims at looking closer into how eight students look upon their own English perceiving skills. A qualitative interview method was used to interview eight students in upper secondary school. The participants were four girls and four boys. The result from the interviews have been presented under three different headings, which are as follows: Motivation, Classroom and Acquisition. A lot of studies have been done on the subject of language learning and it has resulted in many theories, and the ones that seemed relevant for this study have been brought up and connected to the answers the students gave. Most of the students felt motivated to learn English and the main reason was their future job plans. In the classroom, the participants thought that the teacher's behaviour and attitude towards the English subject was the most important factor to motivate them. The interview results showed that the student's thought that the best way to learn English was through media, foremost by speaking and writing with their friends on the computer. Those answers can be connected to something that the Russian psychologist Lev S. Vygotskij presents with the socio-cultural theory, were he promotes the idea that the best way to learn a new language is to interact with other people.
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Karanka, Joni. "Learning in binocular time-to-contact perception." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54808/.

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Time-to-contact (TTC) is defined as the remaining time for an object to reach the observer. This is an important quantity for timing an action such as hitting or catching a ball. This thesis deals with learning processes in TTC perception when binocular vision is available. Chapter 1 studies the learning of TTC in relative discrimination tasks. We did not find learning in this task, but we found that simple correlates of TTC explained the judgments made by the participants. Chapter 2 studies the learning of TTC in absolute estimation tasks. We found that the variable and constant error of the responses reduced with training. Chapter 3 studied the use of feedback in calibrating the timing of TTC estimates. We found that biased timing produced changes in the constant error, suggesting that TTC calibration is guided by feedback. Chapter 4 studied if the reduction of variable error was due to an increased perceptual sensitivity to TTC. However, we failed to find transfer from the absolute estimation tasks to relative discrimination tasks, suggesting that the learning found in Chapter 2 might not be of perceptual origin. In Chapter 5 we studied a large group of participants in laboratory tasks and a natural hitting task. We found that the performance in relative discrimination and absolute estimation tasks could be used to predict hitting skill. This suggests that the perception of TTC can be linked with interceptive timing. Taken together, these results suggest that perceptual sensitivity to TTC changes slightly -if at all- with training, but changes in perceptuo-motor mapping and calibration of the estimates that increase interceptive performance do take place.
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Wozny, David R. "Statistical inference in multisensory perception and learning." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1970597951&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Kulkarni, Tejas Dattatraya. "Learning structured representations for perception and control." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107557.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 117-129).
I argue that the intersection of deep learning, hierarchical reinforcement learning, and generative models provides a promising avenue towards building agents that learn to produce goal-directed behavior given sensations. I present models and algorithms that learn from raw observations and will emphasize on minimizing their sample complexity and number of training steps required for convergence. To this end, I introduce hierarchical variants of deep reinforcement learning algorithms, which produce and utilize temporally extended abstractions over actions. I also present a hybrid model-free and model-based deep reinforcement learning model, which can also be potentially used to automatically extract subgoals for bootstrapping temporal abstractions. I will then present a model-based approach for perception, which unifies deep learning and probabilistic models, to learn powerful representations of images without labeled data or external rewards. Learning goal-directed behavior with sparse and delayed rewards is a fundamental challenge for reinforcement learning algorithms. The primary difficulty arises due to insufficient exploration, resulting in an agent being unable to learn robust value functions. I present the Deep Hierarchical Reinforcement Learning (h-DQN) approach, which integrates hierarchical value functions operating at different time scales, along with goal-driven intrinsically motivated behavior for efficient exploration. Intrinsically motivated agents can explore new behavior for its own sake rather than to directly solve problems. Such intrinsic behaviors could eventually help the agent solve tasks posed by the environment. h-DQN allows for flexible goal specifications, such as functions over entities and relations. This provides an efficient space for exploration in complicated environments. I will demonstrate h-DQN's ability to learn optimal behavior given raw pixels in environments with very sparse and delayed feedback. I will then introduce the Deep Successor Reinforcement (DSR) learning approach. DSR is a hybrid model-free and model-based RL algorithm. It learns the value function of a state by taking the inner product between the state's expected future feature occupancy and the corresponding immediate rewards. This factorization of the value function has several appealing properties - increased sensitivity to changes in the reward structure and potentially the ability to automatically extract subgoals for learning temporal abstractions. Finally, I argue for the need for better representations of images, both in reinforcement learning tasks and in general. Existing deep learning approaches learn useful representations given lots of labeled data or rewards. Moreover, they also lack the inductive biases needed to disentangle causal structure in images such as objects, shape, pose and other intrinsic scene properties. I present generative models of vision, often referred to as analysis-by-synthesis approaches, by combining deep generative methods with probabilistic modeling. This approach aims to learn structured representations of images given raw observations. I argue that such intermediate representations will be crucial to scale-up deep reinforcement learning algorithms, and to bridge the gap between machine and human learning.
by Tejas Dattatraya Kulkarni.
Ph. D.
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Ayeme, Bukola. "Teachers` Perception of Outdoor Learning : Benefits and Challenges of Outdoor Learning." Thesis, Linköpings universitet, Institutionen för beteendevetenskap och lärande, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166745.

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Outdoor learning has become very visible in recent times ,it is seen in different public medias such as magazines, on television, on various websites on internet, in the press and on public notice boards in different countries, accompanying different advertisements displaying a healthy lifestyle especially in early years of studies ( preschool ).The author seeks to address the perception of  Erasmus project “Dehors ” teachers`  experience outdoor, focusing majorly on the benefits and difficulties that these preschool teachers face while teaching outdoors. Furthermore, teachers are known to be role-models for their students and their opinion about their jobs matters a lot in displaying their duties as educators. Preschool children aged 0-6 years spend more time in school more than home, at least a minimum of five days in a week so ultimately attitudes of teachers largely have a positive or negative effect on  school children.  The aim of the present dissertation project is to explore how the teachers perceive outdoor learning based on their experiences outdoors. This study explored the components that characterize teachers` perception of outdoor learning. This research includes two set of interviews which were used to investigate both teachers` outdoor activities performed in Latvia and Swedish preschools. Outdoor learning has made a distinctive difference between the traditional learning approach of “stand and deliver” model which has systematically been changed to “guide on the side” model which educationalist view as a good method of impacting knowledge to learners, instead of giving knowledge as it was practiced before but in recent times, outdoor leaning processes helps to create an atmosphere for co-learning and not an isolated endeavours which is gradually  been replaced by outdoor learning approach of  “tell me and I will forget with “show me and I will remember”. These results provided a great insight on teachers` experiences of outdoor learning in the nature and on asphalt. It can be concluded that outdoor learning approach can be adaptable in the Latvian and Swedish contexts in promoting the development of preschool teachers therefore, there is a need for further research to promote effectiveness of outdoor teaching in Latvia and  Swedish preschools.
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Kacelnik, Oliver. "Perceptual learning in sound localization." Thesis, University of Oxford, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270638.

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McGuire, Grant Leese. "Phonetic category learning." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1190065715.

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Pilling-Cormick, Jane. "Development of the Self-Directed Learning Perception Scale." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ41543.pdf.

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Books on the topic "Perception and learning"

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Apolloni, Bruno, Ashish Ghosh, Ferda Alpaslan, Lakhmi C. Jain, and Srikanta Patnaik, eds. Machine Learning and Robot Perception. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b137627.

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An odyssey in learning and perception. Cambridge, Mass: MIT Press, 1991.

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Learning to see creatively. New York, NY: Amphoto, 1988.

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Saufi, Roselina Ahmad. Students' perception on higher learning education: Data analysis. Kota Kinabalu]: Universiti Malaysia Sabah, 2003.

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Pinard, Minola. Speech and language learning : non-linguistic versus linguistic processes. Québec: Centre international de recherche en aménagement linguistique, 1990.

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Petersen, Jørgen. Visuel perception og læsning: Opstilling og afprøvning af et testbatteri til undersøgelse af visuel perception. København: Institut for dansk sprog og litteratur, Danmarks lærerhøjskole, 1987.

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Anzai, Yūichirō. Pattern recognition and machine learning. Boston: Academic Press, 1992.

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Temporal-pattern learning in neural models. Berlin: Springer-Verlag, 1985.

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Genís, Carme Torras i. Temporal-pattern learning in neuralmodels. Berlin: Springer-Verlag, 1985.

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D, Pick Anne, ed. An ecological approach to perceptual learning and development. Oxford: Oxford University Press, 2000.

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Book chapters on the topic "Perception and learning"

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Nishimoto, Ryunosuke, and Jun Tani. "Schemata Learning." In Perception-Action Cycle, 219–41. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1452-1_7.

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Ádám, György. "Visceral Perception through Learning." In Visceral Perception, 87–102. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-2903-0_8.

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Trevelyan, James P. "Neglected perception skills." In Learning Engineering Practice, 30–34. Boca Raton : CRC Press, [2021]: CRC Press, 2020. http://dx.doi.org/10.1201/b22622-5.

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Turk-Browne, Nicholas B. "Statistical Learning in Perception." In Encyclopedia of the Sciences of Learning, 3182–85. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_1707.

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Martin, Tom. "Perception as Understanding." In Craft Learning as Perceptual Transformation, 105–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64283-9_5.

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Giordana, Attilio, and Alessandro Serra. "Learning from Mistakes." In Human and Machine Perception 3, 89–102. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1361-2_7.

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Schölkopf, Bernhard. "Statistical Learning and Kernel Methods." In Data Fusion and Perception, 3–24. Vienna: Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-2580-9_1.

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Gaschler, Robert, Mariam Katsarava, and Veit Kubik. "Sensation and Perception." In International Handbook of Psychology Learning and Teaching, 1–26. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26248-8_6-1.

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Singh, Leher. "Early Word Recognition and Word Learning in Mandarin Learning Children." In Speech Perception, Production and Acquisition, 199–218. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7606-5_11.

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Giurfa, Martin. "Visual learning in social insects: From simple associations to higher-order problem solving." In Sensory Perception, 109–33. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-211-99751-2_7.

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Conference papers on the topic "Perception and learning"

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Cope, Chris, and Peter Ward. "Teachers' Perceptions of Learning Technologies: An Informing Issue in High School Education." In 2001 Informing Science Conference. Informing Science Institute, 2001. http://dx.doi.org/10.28945/2363.

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A study of the perceptions of learning technologies of a group of high school teachers was undertaken. Underlying the study was the research-based notion that enhanced learning outcomes are likely only if learning technologies are perceived as a means for students to seek the meaning of the subject material. The teachers were interviewed about their perceptions at the beginning and end of a two year period. The interview transcripts were analyzed using phenomenographic research approaches to identify critical variation in perception. The teachers' perceptions of learning technologies were found to have unrelated "what" and "how" components. The "what" component concerned perception of technology. The "how" component concerned perception of the nature of enhanced learning. The various perceptions were found to be inadequate with regard to the "how" component and unlikely to lead to enhanced student learning outcomes. The research findings lead to the suggestion that the teachers need professional development in the nature of enhanced learning and how learning technologies can be used in the classroom to facilitate better learning outcomes.
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Tascini, Guido, Floriana Esposito, Vito Roberto, and Primo Zingaretti. "Machine Learning and Perception." In Conference on Machine Learning abd Perception. WORLD SCIENTIFIC, 1996. http://dx.doi.org/10.1142/9789812797940.

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Murphy, William, Mark D. Halling-Brown, Emma Lewis, Premkumar Elangovan, Kenneth C. Young, David R. Dance, and Kevin Wells. "Using transfer learning for a deep learning model observer." In Image Perception, Observer Performance, and Technology Assessment, edited by Robert M. Nishikawa and Frank W. Samuelson. SPIE, 2019. http://dx.doi.org/10.1117/12.2511750.

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Ora, Ariel, Roland Sahatcija, and Anxhela Ferhataj. "Learning Style and Perception on Hybrid Learning." In University for Business and Technology International Conference. Pristina, Kosovo: University for Business and Technology, 2017. http://dx.doi.org/10.33107/ubt-ic.2017.112.

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Gunderman, Richard B. "Learning to see." In Image Perception, Observer Performance, and Technology Assessment, edited by Robert M. Nishikawa and Frank W. Samuelson. SPIE, 2018. http://dx.doi.org/10.1117/12.2299599.

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López, Marta, Guillermo Bautista, and Anna Escofet. "TEACHERS’ PERCEPTION OF LEARNING SPACES." In 11th International Conference on Education and New Learning Technologies. IATED, 2019. http://dx.doi.org/10.21125/edulearn.2019.2137.

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Hu, Hong, and Zhongzhi Shi. "Perception Learning as Granular Computing." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.895.

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Mokhtar, Siti Fairus, Noor Rasidah Ali, and Nurazlina Abdul Rashid. "Perception determinants in learning mathematics." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON CONDENSED MATTER PHYSICS 2014 (ICCMP 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4915867.

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Sharifrazi, Farnaz, and Suki Stone. "Students Perception of Learning Online." In ICCTA 2019: 2019 5th International Conference on Computer and Technology Applications. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3323933.3324087.

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Zhou, Weimin, Hua Li, and Mark A. Anastasio. "Learning the Hotelling observer for SKE detection tasks by use of supervised learning methods." In Image Perception, Observer Performance, and Technology Assessment, edited by Robert M. Nishikawa and Frank W. Samuelson. SPIE, 2019. http://dx.doi.org/10.1117/12.2512607.

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Reports on the topic "Perception and learning"

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Ozawa, Michiyo. Japanese Students' Perception of Their Language Learning Strategies. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.7036.

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Berenji, Hamid R. Perception-based Co-evolutionary Reinforcement Learning for UAV Sensor Allocation. Fort Belvoir, VA: Defense Technical Information Center, February 2003. http://dx.doi.org/10.21236/ada411839.

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Rodríguez Buitrago, Carolina, Clara Isabel Onatra Chavarro, and Sandra Marina Palencia González. Pre-Service Language Teachers’ Perceptions towards Self-Regulated Learning: Paving the way for Flipped Learning. Institucion Universitaria Colombo Americana, June 2019. http://dx.doi.org/10.26817/paper.07.

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Michaelson, Dawn M., and Karla P. Teel. Active learning in an apparel production management course: Student perceptions, instructor training, and learning outcomes. Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-352.

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Cavallo, Alberto, Guillermo Cruces, and Ricardo Perez-Truglia. Learning from Potentially-Biased Statistics: Household Inflation Perceptions and Expectations in Argentina. Cambridge, MA: National Bureau of Economic Research, March 2016. http://dx.doi.org/10.3386/w22103.

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Van Cleave, Thomas. Short-Term International Service-Learning: Faculty Perceptions of and Pedagogical Strategies for the Design and Implementation of Successful Learning Experiences. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1055.

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Romli, Muhammad Hibatullah, Farahiyah Wan Yunus, Manraj Singh Cheema, Hafizah Abdul Hamid, Muhammad Zulfadli Mehat, Nur Fariesha Md Hashim, Mohamad Hasif Jaafar, Chan Choong Foong, and Wei-Han Hong. A protocol of meta-synthesis on the perceptions and experience of healthcare students in Southeast Asia regarding technology-based learning. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2021. http://dx.doi.org/10.37766/inplasy2021.2.0053.

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Führ, Martin, Julian Schenten, and Silke Kleihauer. Integrating "Green Chemistry" into the Regulatory Framework of European Chemicals Policy. Sonderforschungsgruppe Institutionenanalyse, July 2019. http://dx.doi.org/10.46850/sofia.9783941627727.

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20 years ago a concept of “Green Chemistry” was formulated by Paul Anastas and John Warner, aiming at an ambitious agenda to “green” chemical products and processes. Today the concept, laid down in a set of 12 principles, has found support in various arenas. This diffusion was supported by enhancements of the legislative framework; not only in the European Union. Nevertheless industry actors – whilst generally supporting the idea – still see “cost and perception remain barriers to green chemistry uptake”. Thus, the questions arise how additional incentives as well as measures to address the barriers and impediments can be provided. An analysis addressing these questions has to take into account the institutional context for the relevant actors involved in the issue. And it has to reflect the problem perception of the different stakeholders. The supply chain into which the chemicals are distributed are of pivotal importance since they create the demand pull for chemicals designed in accordance with the “Green Chemistry Principles”. Consequently, the scope of this study includes all stages in a chemical’s life-cycle, including the process of designing and producing the final products to which chemical substances contribute. For each stage the most relevant legislative acts, together establishing the regulatory framework of the “chemicals policy” in the EU are analysed. In a nutshell the main elements of the study can be summarized as follows: Green Chemistry (GC) is the utilisation of a set of principles that reduces or eliminates the use or generation of hazardous substances in the design, manufacture and application of chemical products. Besides, reaction efficiency, including energy efficiency, and the use of renewable resources are other motives of Green Chemistry. Putting the GC concept in a broader market context, however, it can only prevail if in the perception of the relevant actors it is linked to tangible business cases. Therefore, the study analyses the product context in which chemistry is to be applied, as well as the substance’s entire life-cycle – in other words, the six stages in product innovation processes): 1. Substance design, 2. Production process, 3. Interaction in the supply chain, 4. Product design, 5. Use phase and 6. After use phase of the product (towards a “circular economy”). The report presents an overview to what extent the existing framework, i.e. legislation and the wider institutional context along the six stages, is setting incentives for actors to adequately address problematic substances and their potential impacts, including the learning processes intended to invoke creativity of various actors to solve challenges posed by these substances. In this respect, measured against the GC and Learning Process assessment criteria, the study identified shortcomings (“delta”) at each stage of product innovation. Some criteria are covered by the regulatory framework and to a relevant extent implemented by the actors. With respect to those criteria, there is thus no priority need for further action. Other criteria are only to a certain degree covered by the regulatory framework, due to various and often interlinked reasons. For those criteria, entry points for options to strengthen or further nuance coverage of the respective principle already exist. Most relevant are the deltas with regard to those instruments that influence the design phase; both for the chemical substance as such and for the end-product containing the substance. Due to the multi-tier supply chains, provisions fostering information, communication and cooperation of the various actors are crucial to underpin the learning processes towards the GCP. The policy options aim to tackle these shortcomings in the context of the respective stage in order to support those actors who are willing to change their attitude and their business decisions towards GC. The findings are in general coherence with the strategies to foster GC identified by the Green Chemistry & Commerce Council.
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Nagahi, Morteza, Raed Jaradat, Mohammad Nagahisarchoghaei, Ghodsieh Ghanbari, Sujan Poudyal, and Simon Goerger. Effect of individual differences in predicting engineering students' performance : a case of education for sustainable development. Engineer Research and Development Center (U.S.), May 2021. http://dx.doi.org/10.21079/11681/40700.

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The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.
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Means, Barbara, and Julie Neisler. Suddenly Online: A National Survey of Undergraduates During the COVID-19 Pandemic. Digital Promise, July 2020. http://dx.doi.org/10.51388/20.500.12265/98.

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Digital Promise and Langer Research Associates developed the “Survey of Student Perceptions of Remote Teaching and Learning” to capture the experiences of undergraduates taking courses that transitioned to online instruction in response to the COVID-19 pandemic. The survey explores the nature of college courses as they were taught during the COVID-19 outbreak, the pervasiveness of various challenges undergraduates faced after the transition to remote instruction, and course features associated with higher levels of student satisfaction. Data analyses compared experiences of students from low-income, underrepresented, or rural backgrounds to those of students with none of these characteristics. This survey was administered in the spring of 2020 to a random national sample of 1,008 undergraduates, age 18 and older, who were taking college courses for credit that included in-person class sessions when the COVID-19 pandemic hit and had to finish the course by learning at a distance.
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