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The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for amplifying human potential." Not all students or seekers of knowledge receive the education necessary to help them realize their full potential, be it due to a lack of resources or lack of access to high quality teaching. The dearth in high-quality educational content, teaching aids, and methodologies, and non-availability of objective feedback on how they could become better teachers, deprive our teachers from achieving their full potential. The administrators and policy makers lack tools for making optimal decisions such as optimal class sizes, class composition, and course sequencing. All these handicap the nations, particularly the economically emergent ones, who recognize the centrality of education for their growth. EDM-2023 has striven to focus on concepts, principles, and techniques mined from educational data for amplifying the potential of all the stakeholders in the education system. The spotlights of EDM-2023 include: (1) Five keynote talks by outstanding researchers of eminence; (2) A plenary Test of Time award talk and a Banquet talk; (3) Five tutorials (foundational as well as advanced); (4) Four thought provoking panels on contemporary themes; (5) Peer reviewed technical paper and poster presentations; (6) Doctoral students consortium; and (7) An enchanting cultural programme. [Individual papers are indexed in ERIC.]

This paper proposed the question "How do we teach logical thinking and sophisticated mathematics to unsophisticated college students?" One answer among many is through the writing of computer programs. The writing of computer algorithms is mathematical problem solving and logic in disguise and it may attract students who would otherwise stop taking mathematics courses after their required sequence is finished. In college classrooms in the United States, there is often an over-involvement with the calculation aspect of mathematics, especially in today's technical environment. The emphasis should fall on the teachers' developing of logic in students. Just like mathematical algorithms, computer algorithms however simple, employ logical steps which will result in the desired conclusion. Mathematics teachers should take advantage of the inumerable opportunities, even in a beginner's computer programming course, to play with algorithms that may aid students in the development of logical ways to approach mathematical problems. (MA)

The sixth session of IT@EDU98 consisted of seven papers on the topic of the learning machine--Vietnamese based human-computer interface, and was chaired by Phan Viet Hoang (Informatics College, Singapore). "Knowledge Based Approach for English Vietnamese Machine Translation" (Hoang Kiem, Dinh Dien) presents the knowledge base approach, which consists of concepts such as things, actions, relations, and attributes, organized on the structure of inheritance hierarchy. "A Learning Algorithm for Feature Selection Based on Genetic Approach" (Nguyen Dinh Thuc, Le Hoai Bac) presents a genetic algorithm that chooses relevant features from a set of given features, for feature selection based on the correlation among the features and between every feature and given target curve. "Artificial Neural Network for Color Classification" (Tran Cong Toai) examines several neural network models, their learning schemes, and their effectiveness in color classification. "Synthesizing and Recognizing Vietnamese Speech" (Hoang Kiem, Nguyen Minh Triet, Vo Tuan Kiet, Thai Hung Van, Luu Duc Hien, Bui Tien Len) presents algorithms applied successfully in Vietnamese isolated word recognition and Vietnamese synthesis. "On-Line Character Recognition" (Nguyen Thanh Phuong) presents a real-time handwriting character recognition system based on a structural approach. "Data Mining and Knowledge Acquisition from a Database" (Hoang Kiem, Do Phuc) considers how to use multi-dimensional data model (MDDM) for mining rules in a large database. "Genetic Algorithm for Initiative of Neural Networks" (Nguyen Dinh Thuc, Tan Quang Sang, Le Ha Thanh, Tran Thai Son) describes a procedure for initiative of neural networks based on genetic algorithms, based on the correlation between every weight and error function. (SWC)

The present study was an exploratory study of the content-specific knowledge structures of three teacher educators (two in math and one in science). Pathfinder, a method for eliciting associative memory networks, was used to describe the knowledge structures of the teacher educators. Pathfinder was also used to determine changes in knowledge structures of students enrolled in a teaching methodology class taught by each educator. Finally, a measure of the correspondence between students' knowledge structures and those of the teacher educators was correlated with students' performances in the courses. For two teacher educators, students' knowledge structures corresponded more closely with that of the teacher educator after the course than before. For one teacher educator, students exhibited little change in knowledge structure correspondence. Also, students who corresponded most to teacher educators performed better in their respective courses. The findings point to the need for further study of the acquisition of knowledge in undergraduate students and the processes associated with the transmission of knowledge in math and science teacher-education programs. Contains 3 figures, and 19 references. (Author/SLD)

This publication contains the substance of all papers submitted at the fall 1974 Association of Teachers of Mathematics in New England (ATMNE) conference. As the title indicates, the focus of the publication is directed toward mathematical applications. The 25 papers cover topics ranging from applications at the elementary school level to those involving college level mathematics. Subjects of the papers include: function concepts in intermediate grades; mathematical modeling for election decisions; mathematics applications to music, art, grocery store arithmetic, vocational-technical school, economics, communications, ecology, and traffic flow; research and applications; Euclidian geometry; audio-tutorial instruction; computing pi; tanagrams; UISCM materials; the Developing Mathematical Processes program; and computer approximations. Some of the articles include bibliographies and/or references. (JBW)