AI & learning: A preferred future

TL;DR: The article explores natural language processing (NLP), data-driven learning (DDL), automated writing evaluation (AWE), computerized dynamic assessment (CDA), intelligent tutoring systems (ITSs), automatic speech recognition (ASR), and chatbots to suggest that AI will be continuously integrated into language education and AI technologies and applications will have a profound impact on language learning and teaching.

TL;DR: In this paper , the authors examined 18 experienced teachers' perceptions of teaching artificial intelligence and identified effective designs to support AI instruction and found that effective AI instructional design should encompass five important components: (1) obstacles to and facilitators of participation in teaching AI, (2) interactive design thinking processes, (3) teachers' knowledge of teaching AI; (4) orienteering AI knowledge for social good; and (5) the holistic understanding.

TL;DR: It is recommended that faculty members’ readiness to integrate AI and their knowledge of and skills concerning AI and how to use it to improve educational institution outcomes be enhanced.

TL;DR: Dual coding theory (DCT) as mentioned in this paper explains human behavior and experience in terms of dynamic associative processes that operate on a rich network of modality-specific verbal and nonverbal representations.

TL;DR: This paper provides a review of how statistical models can be “trained” on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph) and how such statistical models of graphs can be combined with text-based information extraction methods for automatically constructing knowledge graphs from the Web.

TL;DR: The notion that neocortical operations are essentially multisensory is examined, which forces us to abandon the notion that the senses ever operate independently during real-world cognition.

TL;DR: The phenomena of the emergence of the use of artificial intelligence in teaching and learning in higher education is explored and educational implications of emerging technologies on the way students learn and how institutions teach and evolve are investigated.