This paper reviews literature in cognitive science, human-computer interaction (HCI) and natural-language processing (NLP) to consider how analogical reasoning (AR) could help inform the design of communication and learning technologies, as well as online communities and digital platforms. First, analogical reasoning (AR) is defined, and use-cases of AR in the computing sciences are presented. The concept of schema is introduced, along with use-cases in computing. Finally, recommendations are offered for future work on using analogical reasoning and schema methods in the computing sciences.
Human-centered explanation does not fit all: The interplay of sociotechnical, cognitive, and individual factors in the effect AI explanations in algorithmic decision-making
University of Pittsburgh（匹兹堡大学）；Northeastern University（东北大学）；Syracuse University（Syracuse大学）
NuHF Claw: A Risk Constrained Cognitive Agent Framework for Human Centered Procedure Support in Digital Nuclear Control Rooms
Institute of Nuclear and New Energy Technology, Tsinghua University（清华大学核能与新能源技术研究院）；National Key Laboratory of Human Factors Engineering（人因工程国家重点实验室）；Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所）
Can AI detect pain and express pain empathy? A review from emotion recognition and a human-centered AI perspective
Institute of Psychology, Chinese Academy of Sciences（中国科学院心理研究所）；University of Chinese Academy of Sciences（中国科学院大学）；University of Oxford（牛津大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Hamburg（汉堡大学）；University of Macau（澳门大学）
Remote Sensing Image Intelligent Interpretation with the Language-Centered Perspective: Principles, Methods and Challenges
School of Geosciences and Info-Physics, Central South University（中南大学地球科学与信息物理学院）；Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University（西南交通大学地质科学与环境工程学院）；School of Earth and Space Sciences, Peking University（北京大学地球与空间科学学院）；Institute of Remote Sensing Information Processing (IRSIP), Wuhan University（武汉大学遥感信息处理研究所）
See What I Mean? CUE: A Cognitive Model of Understanding Explanations
Fraunhofer Heinrich Hertz Institute（弗劳恩霍夫海因里希·赫兹研究所）；Technische Universität Berlin（柏林技术大学）；BIFOLD – Berlin Institute for the Foundations of Learning and Data（柏林学习与数据基础研究所）；Centre of eXplainable Artificial Intelligence, Technological University Dublin（可解释人工智能中心，都柏林技术大学）
HARMONIC: Cognitive and Control Collaboration in Human-Robotic Teams
Cognitive Science Department（认知科学系）；Department of Computer Science（计算机科学系）；Rensselaer Polytechnic Institute（拉特格斯理工学院）；University of Texas at Austin（德克萨斯大学奥斯汀分校）
Revisit Systematic Generalization via Meaningful Learning
University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；Alibaba Group（阿里巴巴集团）；Shanghai Jiao Tong University（上海交通大学）；Alberta Machine Intelligence Institute（阿尔伯塔机器智能研究所）；University of Alberta（阿尔伯塔大学）
Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models
University of British Columbia（不列颠哥伦比亚大学）；Zuse School（Zuse学校）；Qatar Computing Research Institute (QCRI)（卡塔尔计算研究所）；Hamad Bin Khalifa University（哈马德·本·哈利法大学）
