The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…

University Examination Timetabling Problem is the most important combinational problem to develop a conflict-free timetable to execute all of the exams in and with the limited timeslots and other resources for universities, colleges or schools. It is also an important Nondeterministic Polynomial Time (NP)-hard problem that has no deterministic…

Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…

Considers three powerful techniques--heuristics, context trees, and search via backward chaining--that a knowledge engineer might employ to develop an expert system to automate performance engineering, i.e., the branch of instructional technology that focuses on the problems of business and industry. (MBR)

Reviews the development of artificial intelligence systems and the mechanisms used, including knowledge representation, programing languages, and problem processing systems. Eleven books and 6 journals are listed as sources of information on artificial intelligence. (23 references) (CLB)

Describes SCISOR (System for Conceptual Information Summarization, Organization and Retrieval), a prototype intelligent information retrieval system that extracts useful information from large bodies of text. It overcomes limitations of linguistic coverage by applying a text processing strategy that is tolerant of unknown words and gaps in…

Provides the transcript of an interview with Dr. Lev Landa that addressed issues related to his algorithmico-heuristic theories of learning and instruction, called Landamatics. Highlights include teaching thinking versus knowledge; algorithms; instructional design; improving training and performance in industry, business, and government;…

Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)