Relevant bibliographies by topics / Mobile AI

Contents

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

Academic literature on the topic 'Mobile AI'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Mobile AI"

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Manser Payne, Elizabeth, James W. Peltier, and Victor A. Barger. "Mobile banking and AI-enabled mobile banking." Journal of Research in Interactive Marketing 12, no. 3 (2018): 328–46. http://dx.doi.org/10.1108/jrim-07-2018-0087.

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PurposeThe rapid growth of technology, including artificial intelligence (AI), in the banking industry has played a disrupting role in traditional banking channels. This study aims to investigate factors that influence the attitudes and perceptions of digital natives pertaining to mobile banking and comfort interacting with AI-enabled mobile banking activities.Design/methodology/approachData were collected from 218 digital natives. This paper uses multivariate regression and two separate multiple regression analyses to examine the differential effects of technology-based (i.e. attitudes toward
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Mao, Yingchi, Andri Pranolo, Leonel Hernandez, Aji Prasetya Wibawa, and Zalik Nuryana. "Artificial intelligence in mobile communication: A Survey." IOP Conference Series: Materials Science and Engineering 1212, no. 1 (2022): 012046. http://dx.doi.org/10.1088/1757-899x/1212/1/012046.

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Abstract In this paper, we elaborate on artificial intelligence (AI) techniques used to improve the performance of mobile communication. This article describes brief AI approaches in mobile communication, several classics AI techniques, and the current AI approaches in wireless communication. The techniques contain fuzzy logic, neural networks, reinforcement learning, and AI techniques implemented on mobile communication. Some keys or terms challenges between AI and future mobile communication, not only 5G generation issues but also how the sixth generation (6G) of mobile networks will be driv
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Kara, Saban, and Yunus Yildiz. "From a commodity to addiction: Are mobile phones valuable commodities or sources of addiction for freshman students?" Revista Amazonia Investiga 11, no. 56 (2022): 196–209. http://dx.doi.org/10.34069/ai/2022.56.08.20.

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Mobile phone use has increased exponentially on a global scale in all segments of society since the rise of the first mobile phones in 1970s. Although a wealth of research has been conducted to measure the effects of mobile phones on individuals, a few studies have been carried out to make a connection between similes and mobile phone use. In this respect, this study examined habits of students on mobile phone use through similes at a private university located in Erbil, Iraq. Students employed food, drink, household items and people to illustrate their mobile phone dependence rate. A question
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Lakulu, Muhammad Modi, Ayad Shihan Izkair, Mohd Fadhil Harfiez Abdul Muttalib, and Nur Azlan Zainuddin. "Leveraging AI in mobile learning to support education: A taxonomy of AI applications." Journal of Infrastructure, Policy and Development 8, no. 16 (2024): 7347. https://doi.org/10.24294/jipd7347.

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This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—Scien
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Nagovitsyn, Roman Sergeevich, Dana Kazimirovna Bartosh, Ilya Vladimirovich Evtushenko, and Nataliya Viktorovna Neverova. "Information space of a higher school based on mobile technologies." Revista Amazonia Investiga 9, no. 29 (2020): 359–67. http://dx.doi.org/10.34069/ai/2020.29.05.40.

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This article presents the author’s vision of the content of the information space based on mobile technologies, which includes three synergistically interconnected areas: mobile Internet training, chat training and education based on mobile applications in the format of audio and video training. The purpose of the study: to develop the information space of a higher school based on mobile technologies and experimentally prove the effectiveness of its implementation in the training of students. The scientific novelty of the author’s research lies in the originality of the approach to the formati
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Palshkov, Kostiantyn, Natalia Shetelya, Nataliia Khlus, Iryna Vakulyk, and Inna Khyzhniak. "Impact of mobile apps in higher education: Evidence on learning." Revista Amazonia Investiga 13, no. 74 (2024): 115–28. http://dx.doi.org/10.34069/ai/2024.74.02.10.

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The article reveals the main advantages of using mobile applications in the educational process and shows their significance in increasing the level of knowledge and skills of higher education students; elements of the content of mobile learning are revealed; didactic principles are singled out and factors that educational mobile applications must meet are grouped; didactic features of mobile applications are shown in the educational process of a higher school. The methodological basis of the study is the general theoretical and methodological provisions of philosophy regarding the relationshi
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P, Suraj, Pranav H M, Prathiksha P Shetty, and Suhas B E. "Artificial Intelligence (AI) Enhanced Cognitive Mobile Computing." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem43702.

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The rise of mobile devices and enhanced by the development in Artificial Intelligence (AI) these power-ups have translated into humongous improvements on how people interact with applications. In this paper we explore the incorporation of cognitive computing approaches for creating mobile specific predictive interaction models. Powered by AI, these models seek to predict user activity, interests and demands for the most human like experience in mobile applications. Here, we present an all-inclusive methodology to collect data from mobile sensors design the model with machine learning algorithm
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Zhang, Ye, Jinrui Zhang, Sheng Yue, Wei Lu, Ju Ren, and Xuemin Shen. "Mobile Generative AI: Opportunities and Challenges." IEEE Wireless Communications 31, no. 4 (2024): 58–64. http://dx.doi.org/10.1109/mwc.006.2300576.

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Lu, Jiayi, Wenjing Xiao, Enmin Song, Mohammad Mehedi Hassan, Ahmad Almogren, and Ayman Altameem. "iAgent: When AI Meets Mobile Agent." IEEE Access 7 (2019): 97032–40. http://dx.doi.org/10.1109/access.2019.2926286.

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Baba, Khalid, Nour-Eddine El Faddouli, and Nicolas Cheimanoff. "Mobile-Optimized AI-Driven Personalized Learning: A Case Study at Mohammed VI Polytechnic University." International Journal of Interactive Mobile Technologies (iJIM) 18, no. 04 (2024): 81–96. http://dx.doi.org/10.3991/ijim.v18i04.46547.

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With the rise of mobile learning platforms, it has become increasingly evident that individuals require personalized experiences that are tailored to the strengths and limitations of mobile devices. The present study explores the significant impact that personalized mobile learning environments, powered by artificial intelligence (AI), could have. This study specifically evaluates the impact of an AI-driven personalized educational platform, designed for mobile devices, on the academic achievement and educational progress of students at Mohammed VI Polytechnic University. The platform, designe
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Dissertations / Theses on the topic "Mobile AI"

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Zhang, Yueqian. "Resource Clogging Attacks in Mobile Crowd-Sensing: AI-based Modeling, Detection and Mitigation." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40082.

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Mobile Crowdsensing (MCS) has emerged as a ubiquitous solution for data collection from embedded sensors of the smart devices to improve the sensing capacity and reduce the sensing costs in large regions. Due to the ubiquitous nature of MCS, smart devices require cyber protection against adversaries that are becoming smarter with the objective of clogging the resources and spreading misinformation in such a non-dedicated sensing environment. In an MCS setting, one of the various adversary types has the primary goal of keeping participant devices occupied by submitting fake/illegitimate sensing
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Ogletree, Xavian Alexander. "Human-AI Teaming for Dynamic Interpersonal Skill Training." Wright State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright1621853024907269.

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Freguja, Gabriele <1989&gt. "Il mercato della telefonia mobile: Il catching-up delle imprese cinesi rispetto ai competitors occidentali." Master's Degree Thesis, Università Ca' Foscari Venezia, 2013. http://hdl.handle.net/10579/3799.

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Questo saggio analizza la situazione attuale del mercato della telefonia mobile mondiale; un mercato che negli ultimi anni sembrava all’inizio di una possibile fase di decadenza, trova nuova linfa vitale per crescere grazie alle vendite di apparecchi economici nei paesi emergenti e agli smartphones. L’ipotesi che proprio questi smartphones possano essere il nuovo design dominante del settore, sarà analizzata con strumenti manageriali quali: il ciclo di vita del prodotto e il ciclo di vita tecnologico. Nel settore dello smartphone, siamo stati testimoni della rapida ascesa di molte aziende cin
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Taghavian, Masoud. "VNF placement in 5G Networks using AI/ML." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0421.

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La transition inévitable des dispositifs matériels physiques vers des modules logiciels légers et réutilisables dans le cadre de la virtualisation des fonctions de réseau (NFV) offre d’innombrables possibilités tout en présentant plusieurs défis sans précédent. La satisfaction des attentes de la NFV dans les réseaux post-5G dépend fortement du placement efficace des services de réseau.L’allocation dynamique des ressources physiques pour les demandes de services en ligne exigeant des ressources hétérogènes selon des exigences de qualité de service spécifiques représente l’une des étapes les plu
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Franzoni, Darnois Guillaume. "Progettazione e integrazione di un sistema di Mobile Crowdsensing con una piattaforma IoT orientata ai servizi." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20884/.

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In questi ultimi anni l'uso di dispositivi intelligenti per qualsiasi tipo di attività è aumentato, si sfruttano ad esempio gli smartwatch per ottenere utili informazioni riguardanti il proprio battito cardiaco e monitorare le calorie consumate in base ai passi effettuati. Allo stesso tempo questi dispositivi sono capaci di connettersi fra di loro comunicando dati e dandoci l'opportunità di controllare da remoto determinati comportamenti. Tutti questi dati che viaggiano da un dispositivo all'altro sono estremamente utili e possono aiutare a comprendere meglio la realtà che ci circonda. Special
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Shukla, Saurabh. "Development of a Human-AI Teaming Based Mobile Language Learning Solution for Dual Language Learners in Early and Special Educations." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547127943126526.

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Saveh, Diana. "Anpassning av mobilnotifikationer med hjälp av maskininlärning." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-36451.

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The aim of this study has been to answer the question whether it is possible to obtain notifications that work with the user, instead of against, which can be experienced as stressful and bothersome. To decrease the stressful notifications an application was created which acted as a notification control. The application used machine learning to predict when the user wanted to receive their notifications. For an artificial intelligence to work there needs to be a pattern recognition. In this case the pattern recognition that was used is called the association rule analysis. The association rule
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Bayar, Gokhan. "Configurable Robot Base Design For Mixed Terrain Applications." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/2/12606530/index.pdf.

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Mobile robotics has become a rapidly developing field of interdisciplinary research within robotics. This promising field has attracted the attention of academicy, industry, several government agencies. Currently from security to personal service mobile robots are being used in a variety of tasks. The use of such robots is expected to only increase in the near future. In this study, it is aimed to design and manufacture a versatile robot base. This base is aimed to be the main driving unit for various applications performed both indoors and outdoors ranging from personal service and assistanc
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Djaidja, Taki Eddine Toufik. "Advancing the Security of 5G and Beyond Vehicular Networks through AI/DL." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://www.theses.fr/2024UBFCK009.

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L'émergence des réseaux de cinquième génération (5G) et des réseaux véhiculaire (V2X) a ouvert une ère de connectivité et de services associés sans précédent. Ces réseaux permettent des interactions fluides entre les véhicules, l'infrastructure, et bien plus encore, en fournissant une gamme de services à travers des tranches de réseau (slices), chacune adaptée aux besoins spécifiques de ceux-ci. Les générations futures sont même censées apporter de nouvelles avancées à ces réseaux. Cependant, ce progrès remarquable les expose à une multitude de menaces en matière de cybersécurité, dont bon nom
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Perera, Jayasuriya Kuranage Menuka. "AI-driven Zero-Touch solutions for resource management in cloud-native 5G networks." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0427.

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Le déploiement des réseaux 5G a introduit des architectures cloud-native et des systèmes de gestion automatisés, offrant aux fournisseurs de services de communication une infrastructure évolutive, flexible et agile. Ces avancées permettent une allocation dynamique des ressources, augmentant celles-ci en période de forte demande et les réduisant en période de faible utilisation, optimisant ainsi les CapEx et OpEx. Cependant, une observabilité limitée et une caractérisation insuffisante des charges de travail entravent la gestion des ressources. Une surprovisionnement pendant les périodes creuse
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Books on the topic "Mobile AI"

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Kulkarni, Shrikaant, and P. William. Advances in AI for Cloud, Edge, and Mobile Computing Applications. Apple Academic Press, 2025. https://doi.org/10.1201/9781003637707.

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Istituto nazionale di statistica (Italy). L'indice del costo della vita valevole ai fini dell'applicazione della scala mobile delle retribuzioni: Dalle origini alla cessazione (1945-97). Istituto nazionale di statistica, [2000], 2000.

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Alessandro, Fiorentino, ed. L' arte del mobile intarsiato a Sorrento dal XIX secolo ai nostri giorni: The art of inlaid furniture in Sorrento from the XIX century to date : [exhibition] New York, Italian Trade Commission 5 November-4 December 1987. Guida Editori, 1987.

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Mobile, ai: Suzuki Yuriika shishū. Shichōsha, 1985.

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Bhaumik, Arkapravo. From AI to Robotics: Mobile, Social, and Sentient Robots. Taylor & Francis Group, 2018.

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From AI to robotics: Mobile, social, and sentient robots. CRC Press, 2018.

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Bhaumik, Arkapravo. From AI to Robotics: Mobile, Social, and Sentient Robots. Taylor & Francis Group, 2018.

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Bhaumik, Arkapravo. From AI to Robotics: Mobile, Social, and Sentient Robots. Taylor & Francis Group, 2018.

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Bhaumik, Arkapravo. From AI to Robotics: Mobile, Social, and Sentient Robots. Taylor & Francis Group, 2018.

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Future Fixed and Mobile Broadband Internet, Clouds and IoT/AI. Wiley & Sons, Limited, John, 2024.

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Book chapters on the topic "Mobile AI"

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Kurni, Muralidhar, Mujeeb Shaik Mohammed, and K. G. Srinivasa. "AI for Mobile Learning." In A Beginner's Guide to Introduce Artificial Intelligence in Teaching and Learning. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32653-0_5.

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Palmer, Daniel. "Mobile Photography and AI." In The Routledge Companion to Mobile Media, 2nd ed. Routledge, 2025. https://doi.org/10.4324/9781003166016-58.

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Bliesch, Florian, and Leif Janzik. "AI in Mobile Applications: AI to Go." In AI Changes the Rules of the Game. Carl Hanser Verlag GmbH & Co. KG, 2022. http://dx.doi.org/10.3139/9783446471825.013.

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Zelinsky, A. "Environment mapping with a mobile robot using sonar." In AI '88. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/3-540-52062-7_90.

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Shan, Richard, and Tony Shan. "Edge AI Patterns." In Artificial Intelligence and Mobile Services – AIMS 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45140-9_9.

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Kumari, Sunita, Arush Sachdeva, Anant Bansal, and Deepanshu Pal. "Mobile Healthcare Applications." In 6G-Enabled IoT and AI for Smart Healthcare. CRC Press, 2023. http://dx.doi.org/10.1201/9781003321668-5.

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Campolo, Claudia, Gianmarco Lia, Marica Amadeo, Giuseppe Ruggeri, Antonio Iera, and Antonella Molinaro. "Towards Named AI Networking: Unveiling the Potential of NDN for Edge AI." In Ad-Hoc, Mobile, and Wireless Networks. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-61746-2_2.

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Maire, Frederic, and Gavin Suddrey. "Path Algebra for Mobile Robots." In AI 2015: Advances in Artificial Intelligence. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26350-2_34.

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Yoo, Hoi-Jun. "Mobile Embedded DNN and AI SoCs." In Low Power Circuit Design Using Advanced CMOS Technology. River Publishers, 2022. http://dx.doi.org/10.1201/9781003338772-4.

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Petrenko, Anatolii. "Breathmonitor: AI Sleep Apnea Mobile Detector." In Studies in Computational Intelligence. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94910-5_11.

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Conference papers on the topic "Mobile AI"

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Sayed, Eman, Sara M. Mosaad, and Ahmad N. Gohar. "A Collaborative Human-AI Guided Decision Framework - Gen-Edge-AI." In 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). IEEE, 2024. https://doi.org/10.1109/miucc62295.2024.10783537.

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Metwally, Mariam Alaa, and Milad Ghantous. "Detecting Generative AI in Images." In 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). IEEE, 2024. https://doi.org/10.1109/miucc62295.2024.10783626.

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Ghogare, Snehal, Shivkanya Dhupe, Abhijit Kulkarni, Tanish Shingane, and Renuka Gound. "PlantCare AI: An AI Based Solution for Plant Disease Diagnosis and Assistance." In 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI). IEEE, 2025. https://doi.org/10.1109/icmcsi64620.2025.10883384.

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Almtireen, Natheer, Hashem Altaha, Aws Alissa, Mutaz Ryalat, and Hisham Elmoaqet. "AI-Driven Mobile App for Personalized Health Monitoring." In 2024 22nd International Conference on Research and Education in Mechatronics (REM). IEEE, 2024. http://dx.doi.org/10.1109/rem63063.2024.10735595.

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Pasricha, Sudeep. "AI-Driven Indoor Navigation with Mobile Embedded Systems." In 2024 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS). IEEE, 2024. http://dx.doi.org/10.1109/codes-isss60120.2024.00016.

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Saeed, Sana, Kashif Bilal, Abdallah Namoun, Isa Ali Ibrahim, and Junaid Shuja. "Feature-Centric Mobile Applications Clustering with Generative AI." In 2024 2nd International Conference on Foundation and Large Language Models (FLLM). IEEE, 2024. https://doi.org/10.1109/fllm63129.2024.10852481.

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D, Archana, Deepthi Sri R, Deva Dharani P, Haripriya S, and Vimala Varshini C P. "Decoding Mobile App Performance with Explainable AI (XAI)." In 2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC). IEEE, 2024. http://dx.doi.org/10.1109/icsseecc61126.2024.10649407.

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Makram, Manal, and Ammar Mohammcd. "AI Applications in Medical Reporting and Diagnosis." In 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC). IEEE, 2024. https://doi.org/10.1109/miucc62295.2024.10783552.

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Gaurav, Akshat, Varsha Arya, Brij B. Gupta, and Kwok Tai Chui. "Attention-Enhanced Hybrid AI Model for IoT Security." In 2025 International Wireless Communications and Mobile Computing (IWCMC). IEEE, 2025. https://doi.org/10.1109/iwcmc65282.2025.11059511.

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H, Abhinav Shankar, Mohanprasath R, Pavithran R. A, and G. Manoj Kumar. "AI-Driven Smart Space Allocation Framework." In 2025 6th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI). IEEE, 2025. https://doi.org/10.1109/icmcsi64620.2025.10883090.

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Reports on the topic "Mobile AI"

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Carter, Evan. Long-Term Analysis of a Human-AI Collaboration Study Using a Mobile Game. DEVCOM Army Research Laboratory, 2023. http://dx.doi.org/10.21236/ad1192832.

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Agarwal, Smisha, Madhu Jalan, Holly C. Wilcox, et al. Evaluation of Mental Health Mobile Applications. Agency for Healthcare Research and Quality (AHRQ), 2022. http://dx.doi.org/10.23970/ahrqepctb41.

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Background. Mental health mobile applications (apps) have the potential to expand the provision of mental health and wellness services to traditionally underserved populations. There is a lack of guidance on how to choose wisely from the thousands of mental health apps without clear evidence of safety, efficacy, and consumer protections. Purpose. This Technical Brief proposes a framework to assess mental health mobile applications with the aim to facilitate selection of apps. The results of applying the framework will yield summary statements on the strengths and limitations of the apps and ar
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Fukuda, Koichi. Future Prospects for Smart Agriculture: Focusing on Case Studies in Japan and Asia. Asian Productivity Organization, 2025. https://doi.org/10.61145/jimb5846.

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This report examines the future prospects of smart agriculture, focusing on case studies from Japan and other Asian countries. Since 2019, Japan has promoted smart agriculture through government-supported initiatives, primarily targeting large-scale farms utilizing technologies such as AI, robotics, and satellite systems. However, as most Japanese farmers operate on a small-to-medium scale, there is growing demand for cost-effective, user-friendly solutions. The report highlights innovations including compact robots, AI-driven irrigation systems, and mobile apps for farm management and traceab
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chambers, Colin, and April Lockhart. Review of key machinery safety standards and guidance, and how they reflect on emerging technologies. HSE, 2024. http://dx.doi.org/10.69730/hse.24rr1214.

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Two key regulations supporting machinery safety in the UK are the Supply of Machinery (Safety) Regulations 2008 (SMSR) and the Provision and Use of Work Equipment Regulations 1998 (PUWER). Considering the emergence of new and emerging technologies, particularly autonomous mobile robots (AMR) and autonomous agricultural vehicles (AAV), and the potential utilization of artificial intelligence (AI) for machinery safety, HSE commissioned a study to identify gaps in existing standards and guidance documents.
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Braga, Bianca C., Noora-Lisa Aberman, Alejandra Arrieta, et al. Design of a mobile phone-based Artificial Intelligence (AI) application to assess dietary intake and provide nudges to improve healthy eating choices: Formative research in Ghana and Vietnam. International Food Policy Research Institute, 2021. http://dx.doi.org/10.2499/p15738coll2.134412.

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Ruvinsky, Alicia, Timothy Garton, Daniel Chausse, Rajeev Agrawal, Harland Yu, and Ernest Miller. Accelerating the tactical decision process with High-Performance Computing (HPC) on the edge : motivation, framework, and use cases. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/42169.

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Managing the ever-growing volume and velocity of data across the battlefield is a critical problem for warfighters. Solving this problem will require a fundamental change in how battlefield analyses are performed. A new approach to making decisions on the battlefield will eliminate data transport delays by moving the analytical capabilities closer to data sources. Decision cycles depend on the speed at which data can be captured and converted to actionable information for decision making. Real-time situational awareness is achieved by locating computational assets at the tactical edge. Acceler
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Fang, Mei Lan, Judith Sixsmith, Jacqui Morris, et al. AgeTech, Ethics and Equity: Towards a Cultural Shift in AgeTech Ethical Responsibility. University of Dundee, 2023. http://dx.doi.org/10.20933/100001292.

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Population ageing is a global phenomenon which presents major challenges for the provision of care at home and in the community (ONS, 2018). Challenges include the human and economic costs associated with increasing numbers of older people with poor physical and mental health, loneliness, and isolation challenges (Mihalopoulos et al., 2020). The global ageing population has led to a growth in the development of technology designed to improve the health, well-being, independence, and quality of life of older people across various settings (Fang, 2022). This emerging field, known as “AgeTech,” r
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Vikström, Carina, ed. Bidrag från Högskolepedagogisk utvecklingsdag 2023: Del 1. Karlstads universitet, 2024. https://doi.org/10.59217/sycc4161.

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I föreliggande rapport kan du ta del av sju olika utvecklingsprojekt inom undervisning och examination vid Karlstads universitet. Samtliga bidrag i rapporten har utvecklats från arbeten som presenterats vid Universitetspedagogiska enhetens högskolepedagogiska utvecklingsdag, KauKan (tidigare högskolepedagogisk konferens). I årets första upplaga får vi bland annat en insyn i hur lärare hjälpt studenter att tydligare förstå ett specifikt lärandemål och hur det går att effektivisera arbetet med inlämningsuppgifter i stora studentgrupper med hjälp av automatisk återkoppling och automatisk bedömnin
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