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Статті в журналах з теми "Players' learning"
Bojanić, Milana, and Goran Bojanić. "Self-Learning Mechanism for Mobile Game Adjustment towards a Player." Applied Sciences 11, no. 10 (May 13, 2021): 4412. http://dx.doi.org/10.3390/app11104412.
Повний текст джерелаWu, Tianhang, Hanchen Wang, Jian Yang, Liang Xu, Yumeng Li, and Jun Zhang. "The prisoner’s dilemma game on scale-free networks with heterogeneous imitation capability." International Journal of Modern Physics C 29, no. 09 (September 2018): 1850077. http://dx.doi.org/10.1142/s0129183118500778.
Повний текст джерелаWolitzky, Alexander. "Learning from Others' Outcomes." American Economic Review 108, no. 10 (October 1, 2018): 2763–801. http://dx.doi.org/10.1257/aer.20170914.
Повний текст джерелаSilva, João Vítor Rocha da, and Paulo Canas Rodrigues. "All-NBA Teams’ Selection Based on Unsupervised Learning." Stats 5, no. 1 (February 9, 2022): 154–71. http://dx.doi.org/10.3390/stats5010011.
Повний текст джерелаHurkens, Sjaak. "Learning by Forgetful Players." Games and Economic Behavior 11, no. 2 (November 1995): 304–29. http://dx.doi.org/10.1006/game.1995.1053.
Повний текст джерелаLi, Neill Y., Nicholas J. Lemme, Steven F. Defroda, Elvis Nunez, Davis A. Hartnett, and Brett D. Owens. "Performance After Operative Versus Nonoperative Management of Shoulder Instability in the National Basketball Association." Orthopaedic Journal of Sports Medicine 7, no. 12 (December 1, 2019): 232596711988933. http://dx.doi.org/10.1177/2325967119889331.
Повний текст джерелаSantillan, Luis Alberto Casillas, and Johor Ismael Jara Gonzalez. "Learning Avatar's Locomotion Patterns Through Spatial Analysis in FPS Video Games." International Journal of Organizational and Collective Intelligence 8, no. 1 (January 2018): 28–45. http://dx.doi.org/10.4018/ijoci.2018010103.
Повний текст джерелаKarnuta, Jaret M., Bryan C. Luu, Heather S. Haeberle, Paul M. Saluan, Salvatore J. Frangiamore, Kim L. Stearns, Lutul D. Farrow, et al. "Machine Learning Outperforms Regression Analysis to Predict Next-Season Major League Baseball Player Injuries: Epidemiology and Validation of 13,982 Player-Years From Performance and Injury Profile Trends, 2000-2017." Orthopaedic Journal of Sports Medicine 8, no. 11 (November 1, 2020): 232596712096304. http://dx.doi.org/10.1177/2325967120963046.
Повний текст джерелаHernandez, Jérôme, Mathieu Muratet, Matthis Pierotti, and Thibault Carron. "Can We Detect Non-playable Characters’ Personalities Using Machine And Deep Learning Approaches?" European Conference on Games Based Learning 16, no. 1 (September 29, 2022): 271–79. http://dx.doi.org/10.34190/ecgbl.16.1.627.
Повний текст джерелаStanley, Kenneth, Ryan Cornelius, Risto Miikkulainen, Thomas D’Silva, and Aliza Gold. "Real-Time Learning in the NERO Video Game." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 1, no. 1 (September 28, 2021): 159–60. http://dx.doi.org/10.1609/aiide.v1i1.18736.
Повний текст джерелаДисертації з теми "Players' learning"
Kallunki, K. P. (Kari-Pekka). "Learning English in World of Warcraft:perspectives from the players." Master's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201603111310.
Повний текст джерелаTämän Pro Gradu -tutkielman tavoitteena on tutkia, millä tavoin verkossa pelattava moninpeli World of Warcraft edesauttaa englannin oppimista vieraana kielenä. Samalla tavoitteena on kriittisesti arvioida pelaamisen kautta tapahtuvan kielenoppimisen hyötyjä ja haittoja. Videopelien pelaaminen on yleistynyt 2000-luvulta lähtien, ja esimerkiksi World of Warcraftin pelaajakunnasta noin 35 prosenttia on naispuolisia pelaajia. Videopeleillä on alati laajeneva kohderyhmä, ja englantia opitaan yhä enemmän pelien kautta, joten on aiheellista tutkia kielenoppimista peleissä kouluopetuksen näkökulmasta. Tämä tutkimus perustuukin eurooppalaisilla World of Warcraftin pelaajilla teetettyyn kyselyyn, jossa heitä pyydettiin kertomaan ajatuksiaan, mielipiteitään ja kokemuksiaan liittyen englannin oppimiseen World of Warcraftin kautta. Tutkimuksen eräänä tavoitteena on myös selvittää, onko videopelien avulla tapahtuvaa englannin oppimista syytä pitää uhkana koulujärjestelmän asettamien kielenoppimisen tavoitteiden kannalta vai voitaisiinko videopeleistä ottaa jopa vaikutteita kouluopetukseen. Verkossa pelattavat moninpelit ovatkin yksi kätevimmistä keinoista päästä harjoittelemaan englantia kansainvälisessä kontekstissa. Hampel (2006) ja Furstenberg (1997) sanovat, että tietokonepohjaisissa kielenoppimistilanteissa oppija pääsee toimimaan aktiivisena osallistujana ja saa tehdä yhteistyötä muiden oppijoiden kanssa. Sylvén ja Sundqvist (2012) jatkavat, että World of Warcraft tarjoaa pelaajilleen mahdollisuuksia käyttää englantia aidonkaltaisissa vuorovaikutustilanteissa. Gee (2003, 2007) puolestaan sanoo, että videopelit herättävät pelaajassa aitoa motivaatiota oppimista kohtaan. Gee (2007) myös perustelee videopelien tehokkuutta kielenoppimisen välineenä sanomalla, että kieli on peleissä vahvasti kontekstualisoitua. Pelissä suoritetut toiminnot ja pelin tarjoamat kuvalliset ja äänelliset vihjeet siis tukevat kielen ymmärtämistä ja helpottavat oppimista. Saarenkunnas (2006) toteaakin, että tästä syystä myös nuoret lapset kykenevät pelaamaan englanninkielisiä pelejä. Tutkimuksesta saadut tulokset kuitenkin antavat ristiriitaisen kuvan kielenoppimisesta World of Warcraftissa. Toisaalta pelaaminen on helppo ja mielenkiintoinen tapa oppia uutta ja monimutkaista sanastoa. World of Warcraft myös tarjoaa pelaajilleen sosiaalisen ympäristön, jossa harjoitella englannin puhumista autenttisissa kielenkäyttötilanteissa. Toisaalta taas pelaajien puhuman englannin taso vaihtelee puhujakohtaisesti, eikä pelissä puhuttu kieli noudata aina kaikkia englannin kielioppi- tai oikeinkirjoitussääntöjä. Pelissä myös törmää usein epäsoveliaaseen kielenkäyttöön ja käytökseen, joten pelin kannustavuus kielenoppimisympäristönä voidaan kyseenalaistaa. Kouluopetuksessa voitaisiin kuitenkin ottaa mallia videopelien tavasta luoda motivoivia ja autenttisia kielenkäyttötilanteita. Jatkotutkimuksessa voitaisiinkin selvittää, miten videopeleistä saadut kielenoppimisen hyödyt voitaisiin valjastaa kouluopetuksen käyttöön siten, että vain kielenoppimisen kannalta myönteiset vaikutukset siirtyvät pelistä oppijaan
Lu, Wei-Lwun. "Learning to track and identify players from broadcast sports videos." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/39956.
Повний текст джерелаTaylor, Angela Ruth. "Understanding older amateur keyboard players : music learning and mature adult musical identity." Thesis, UCL Institute of Education (IOE), 2009. http://eprints.ioe.ac.uk/20594/.
Повний текст джерелаGalvao, Afonso Celso Tanus. "Practice in orchestral life : an exploratory study of string players' learning processes." Thesis, University of Reading, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269116.
Повний текст джерелаVidlund, Anna. "English in video and online computer games : Potential enhancement of players’ vocabulary." Thesis, Linnéuniversitetet, Institutionen för språk (SPR), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-28402.
Повний текст джерелаWhetzel, Jonathan Hunt. "Developing intelligent agents for training systems that learn their strategies from expert players." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2662.
Повний текст джерелаHill, Jimmy Matthew. "Extra-curricular activities on the field subcultural learning of in-game infractions among collegiate football players /." Birmingham, Ala. : University of Alabama at Birmingham, 2009. https://www.mhsl.uab.edu/dt/2009m/hill.pdf.
Повний текст джерелаDonnelly, Jilian K. "Understanding Educational Choice Processes of Retired Professional Hockey Players." Diss., Temple University Libraries, 2014. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/260106.
Повний текст джерелаEd.D.
The purpose of this qualitative study was to investigate the processes and influences that underlie the choice of retired elite athletes to further their education and assume the adult learner role. In the current study, focus was applied specifically to professional ice hockey players who were in a period of retirement from active play. Elite athletes often retire at a time when most other professions are just beginning or reaching a level of stability. Research suggests that many retired elite athletes experience a difficult transition to an early retirement from athletics that is fraught with depression and unemployment. A select number of these elite athletes choose to further their educations after their careers have expired. The literature suggests that some of these retired elite athletes find educational programming a valuable coping strategy in the often traumatic post-athletic career adjustment. Unfortunately, this choice is made by only few athletes. It would be desirable to encourage more retired athletes to consider and engage in educational activities; however, currently, there is only very little knowledge on the processes underlying athletes' choice to participate, or not to participate, in education in their retirement years. Using a theoretical framework that includes adult learning theory and adult development theory, in conjunction with expectancy-value theory of motivation, the impact of individual characteristics and environmental opportunities on post-athletic career choices made by professional athletes may be better understood. The primary instrument for data collection was a personal interview with ten retired professional hockey players, conducted over a consecutive six-month period resulting in significant data. Utilizing the constant-comparative method for data analysis, common themes were identified as indicators of educational engagement: Informal Mentorship, Head Injury Related Retirement, and Pre-Transition Planning. In addition to these themes, the findings reflected an alternative adult developmental model possibly unique to professional hockey players. The findings of this study are valuable to the larger conversation regarding adult learners, adult development, and elite athlete career transition.
Temple University--Theses
Llobet, Martí Bernat. "Analysis of the interactivity in a teaching and learning sequence with novice rugby players: the transfer of learning responsibility and control." Doctoral thesis, Universitat de Girona, 2016. http://hdl.handle.net/10803/399791.
Повний текст джерелаAquesta tesi és una compilació de 3 articles, i l'objectiu principal és eñ mecanisme de traspàs de l'aprenentatge. El primer article explica el Rugby Attack Assessment Instrument, una eina que avalua el rendiment col·lectiuen el rugbi en una situació reduïda de 5x5, tenint en compte accions simples i comportaments tàctics més complexos. El segon article explica l'ús del Model Integrat Tècnic-Tàctic utilitzat durant la seqüència d'ensenyament i aprenentatge, i explica els resultats de l'aprenentatge d'aquesta seqüència. Els resultats en un nivell macro revelen que no hi ha millores significatives. Els resultats a nivell micro mostren un increment de la freqüència de determinats comportaments tàctics. El tercer article analitza la interactivitat entre els participants i el traspàs de la responsabilitat de l'aprenentatge de l'entrenador als jugadors. Les unitats d'anàlisi són els segments d'interactivitat. Els resultats mostren que aquest procés està lligat a un lleuger descens de la segmentació i principalment a un traspàs dels moments de reflexió des de segments específics de discussió cap a reflexions dutes a terme durant la pràctica guiada
Millard, Lourens, and Ryan Raffan. "Impact of visual skills training on the visual ability of elite rugby players." Thesis, Nelson Mandela Metropolitan University, 2016. http://hdl.handle.net/10948/12692.
Повний текст джерелаКниги з теми "Players' learning"
1930-, Jones Elizabeth, ed. Master players: Learning from children at play. New York: Teachers College Press, 1997.
Знайти повний текст джерелаBuchanan, John. Learning from legends: Australian cricket. Pyrmont: Fairfax Media Publications, 2009.
Знайти повний текст джерелаStout, Glenn. From hardships to championships: Learning life's lessons. Boston: Houghton Mifflin Harcourt, 2013.
Знайти повний текст джерелаBain, David. Learning the violin: Finger positions in nine scales : a violin learning and teachingaid for violin players everywhere. Burry Port: D. Bain, 1996.
Знайти повний текст джерелаSerious players in the primary classroom: Empowering children through active learning experiences. New York: Teachers College Press, 1990.
Знайти повний текст джерелаSerious players in the primary classroom: Empowering children through active learning experiences. 2nd ed. New York: Teachers College Press, 2000.
Знайти повний текст джерелаWaitzkin, Josh. The art of learning: A journey in the pursuit of excellence. New York: Free Press, 2007.
Знайти повний текст джерелаTrueba, David. Learning to lose: A novel. New York: Other Press, 2009.
Знайти повний текст джерелаLearning to lose. New York: Other Press, 2010.
Знайти повний текст джерелаLearning to lose. London: Portobello, 2011.
Знайти повний текст джерелаЧастини книг з теми "Players' learning"
McArdle, Felicity, Jennifer Sumsion, Sue Grieshaber, Kellie Bousfield, and Paul Shield. "Team Players." In Play: A Theory of Learning and Change, 35–54. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25549-1_4.
Повний текст джерелаMacdonald, Verna. "The Park Bench Players." In Working the Margins of Community-Based Adult Learning, 145–55. Rotterdam: SensePublishers, 2016. http://dx.doi.org/10.1007/978-94-6300-483-1_12.
Повний текст джерелаDecroos, Tom, and Jesse Davis. "Player Vectors: Characterizing Soccer Players’ Playing Style from Match Event Streams." In Machine Learning and Knowledge Discovery in Databases, 569–84. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46133-1_34.
Повний текст джерелаde Vries, Marjolein, and Pieter Spronck. "Deep Learning for Classifying Battlefield 4 Players." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 161–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49616-0_15.
Повний текст джерелаYen, Shi-Jim, Yi-Ling Chen, and Hsin-I. Lin. "Scaffolding Learning for the Novice Players of Go." In Lecture Notes in Computer Science, 139–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-35343-8_15.
Повний текст джерелаDomeshek, Eric, Sowmya Ramachandran, Randy Jensen, and Jeremy Ludwig. "Realistic and Relevant Role-Players for Experiential Learning." In Adaptive Instructional Systems, 55–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50788-6_5.
Повний текст джерелаAleemulla Khan, P., N. Thirupathi Rao, and Debnath Bhattacharyya. "Prediction of Cricket Players Performance Using Machine Learning." In Smart Technologies in Data Science and Communication, 155–62. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2407-3_20.
Повний текст джерелаInal, Yavuz, Turkan Karakus, and Kursat Cagiltay. "Designing Narratology-Based Educational Games with Non-players." In Technologies for E-Learning and Digital Entertainment, 528–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69736-7_56.
Повний текст джерелаMuazu Musa, Rabiu, Anwar P. P. Abdul Majeed, Muhammad Zuhaili Suhaimi, Mohd Azraai Mohd Razman, Mohamad Razali Abdullah, and Noor Azuan Abu Osman. "Anthropometric Variables in the Identification of High-performance Volleyball Players." In Machine Learning in Elite Volleyball, 33–41. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3192-4_5.
Повний текст джерелаCowley, Benjamin Ultan, Darryl Charles, Gerit Pfuhl, and Anna-Mari Rusanen. "Artificial Intelligence in Education as a Rawlsian Massively Multiplayer Game: A Thought Experiment on AI Ethics." In AI in Learning: Designing the Future, 297–316. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09687-7_18.
Повний текст джерелаТези доповідей конференцій з теми "Players' learning"
Huang, Chi-Wen, Cheng-Yu Fan, Yu-Ling Chi, Chia-Jung Wu, and Gwo-Dong Chen. "High-Interactive Gaming Learning: Bring Different Learning Benefits to Team Players and Individual Players." In 2012 IEEE 12th International Conference on Advanced Learning Technologies (ICALT). IEEE, 2012. http://dx.doi.org/10.1109/icalt.2012.176.
Повний текст джерелаLiu, Guiliang, and Oliver Schulte. "Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/478.
Повний текст джерелаKowalski, Jakub, and Andrzej Kisielewicz. "Testing general game players against a Simplified Boardgames player using temporal-difference learning." In 2015 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2015. http://dx.doi.org/10.1109/cec.2015.7257061.
Повний текст джерелаYahyasoltani, Nasim, Manzur Farazi, and Priyanka Annapureddy. "Learning Performance Efficiency of College Basketball Players." In 2021 IEEE 23rd Int Conf on High Performance Computing & Communications; 7th Int Conf on Data Science & Systems; 19th Int Conf on Smart City; 7th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys). IEEE, 2021. http://dx.doi.org/10.1109/hpcc-dss-smartcity-dependsys53884.2021.00197.
Повний текст джерелаRanieri, Maria, and Cristina Gaggioli. "STEREOTYPES, VIDEOGAMES AND AWARE PLAYERS IN HIGHER EDUCATION." In 12th International Conference on Education and New Learning Technologies. IATED, 2020. http://dx.doi.org/10.21125/edulearn.2020.1279.
Повний текст джерелаAlhajry, Majed, Faisal Alvi, and Moataz Ahmed. "TD(λ) and Q-learning based Ludo players." In 2012 IEEE Conference on Computational Intelligence and Games (CIG). IEEE, 2012. http://dx.doi.org/10.1109/cig.2012.6374142.
Повний текст джерелаWang, Pengcheng, Jonathan Rowe, Wookhee Min, Bradford Mott, and James Lester. "Interactive Narrative Personalization with Deep Reinforcement Learning." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/538.
Повний текст джерелаHocquette, Céline. "Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?" In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/909.
Повний текст джерелаNosu, Kiyhoshi, Tomoya Kurokawa, Hiroto Horita, Yoshitarou Ohhazama, and Hiroki Takeda. "Real Time Emotion-Diagnosis of Video Game Players from their Facial Expressions and its Applications to Voice Feed-Backing to Game Players." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370512.
Повний текст джерелаLuo, Yudong, Oliver Schulte, and Pascal Poupart. "Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/464.
Повний текст джерелаЗвіти організацій з теми "Players' learning"
Devereux, Stephen, and Anna Wolkenhauer. Agents, Coercive Learning, and Social Protection Policy Diffusion in Africa. Institute of Development Studies (IDS), December 2021. http://dx.doi.org/10.19088/ids.2021.068.
Повний текст джерелаDouglas, Thomas, and Caiyun Zhang. Machine learning analyses of remote sensing measurements establish strong relationships between vegetation and snow depth in the boreal forest of Interior Alaska. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41222.
Повний текст джерелаKaffenberger, Michelle, Danielle Sobol, and Deborah Spindelman. The Role of Low Learning in Driving Dropout: A Longitudinal Mixed Methods Study in Four Countries. Research on Improving Systems of Education (RISE), April 2021. http://dx.doi.org/10.35489/bsg-rise-wp_2021/070.
Повний текст джерелаIsmailova, L. Yu, O. O. Zhuravleva, O. I. Bazhenova, V. S. Zaytsev, and I. O. Sleptsov. educational computer game "family meeting" (version 1.0). SIB-Expertise, July 2022. http://dx.doi.org/10.12731/er0578.04072022.
Повний текст джерелаYorke, Lynda, Simon Tate, and Martin Davis. New to teaching geography. Royal Geographical Society (with IBG), December 2021. http://dx.doi.org/10.55203/gvkz5128.
Повний текст джерелаFreed, Danielle. K4D Strengthens Partners’ Ability to Deliver Improved Results for Inclusion in Crises. Institute of Development Studies, September 2022. http://dx.doi.org/10.19088/k4d.2022.161.
Повний текст джерелаBabu M.G., Sarath, Debjani Ghosh, Jaideep Gupte, Md Asif Raza, Eric Kasper, and Priyanka Mehra. Kerala’s Grass-roots-led Pandemic Response: Deciphering the Strength of Decentralisation. Institute of Development Studies (IDS), June 2021. http://dx.doi.org/10.19088/ids.2021.049.
Повний текст джерелаFedorenko, Elena G., Nataliia V. Kaidan, Vladyslav Ye Velychko, and Vladimir N. Soloviev. Gamification when studying logical operators on the Minecraft EDU platform. [б. в.], July 2021. http://dx.doi.org/10.31812/123456789/4624.
Повний текст джерелаAvellán, Leopoldo, Zulima Leal Calderon, and Giulia Lotti. Why do some Development Projects Disburse Funds Faster than Others. Inter-American Development Bank, November 2021. http://dx.doi.org/10.18235/0003839.
Повний текст джерелаRoschelle, Jeremy, Britte Haugan Cheng, Nicola Hodkowski, Julie Neisler, and Lina Haldar. Evaluation of an Online Tutoring Program in Elementary Mathematics. Digital Promise, April 2020. http://dx.doi.org/10.51388/20.500.12265/94.
Повний текст джерела