본 연구는 혼합주석 (combined glossing)이 읽기 자료에 적용되었을 때 즉각적 어휘 회상(immediate word recall) 과 2주 후 어휘 기억유지 (word retention) 에 주는 효과에 대해 살펴보았다. 연구를 위해 읽기 자료의 내용 이해에 중요한 단어들을 학습 목표의 어휘로 삼고 이들이 4번 반복적으로 나오도록 약간의 수정이 이루어 졌고, 세 가지 혼합주석이 다음과 같이 적용되었다: (1)네 번의 L1 주석 (4G); (2) L1 주석 한번과 의미 써보기 (GR); (3) L1 주석 한번과 3번 볼드체 (GB3).초급을 조금 벗어난 (공인토익 450-470점) 30 명의 학습자들에게서 얻은 데이터 분석 결과, GR 주석이 즉각적인 수용적, 생산적 어휘 회상에 있어 가장 의미 있는 결과를 얻었고, 다음으로 4G 와 GB3순서로 나타났다. 장기 어휘 기억 유지에 있어서는, 수용적 그리고 생산적 어휘 기억 유지에 있어 GB3 주석이 가장 효과적이었고 다음으로 4G 와 GR 순서로 의미가 있었다. 이러한 결과는 읽기 자료에 L1 주석과 의미적 강화인 단어 회상하여 써보기 (written retrieval), 또는 시각적 강화인 볼드체의반복 (frequent boldface) 과 혼합될 때 EFL 학습자의 어휘 학습에 많은 도움이 된다는 것을 나타내고 있다.

The purpose of the study is to explore whether input enhancement as a subtype of FonF can be proven feasible and productive as part of normal classroom work and whether it can assist in learners` long-term progress in English. 80 freshmen who enrolled general English at a Korean university were divided into an experimental group and a control group and read the text in one of two conditions: no enhancement, relative-clause enhancement. The results demonstrated the translation task scores obviously showed the effect of input enhancement. The enhanced text of relative-clause led to learning relative-clause as a target linguistic structure. Second, the effect of relative-clause enhancement text was significant on reading comprehension test as well as on translation task. The interesting result was that the effects on relative-clause learning and reading comprehension were retained in the follow-up posttest conducted four weeks later. The study proposed that learners` linguistic developmental system have been affected by the enhanced relative-clause text generated by learners` need and that their interlanguage system be reconstructed.

This paper describes a program which learns good strategies for two-poison, deterministic, zero-sum board games of perfect information. The program learns by simply playing the game against either a human or computer opponent. The results of the program's teaming of a lot of games are reported. The program consists of search kernel and a move generator module. Only the move generator is modified to reflect the rules of the game to be played. The kernel uses a temporal difference procedure combined with a backpropagation neural network to team good evaluation functions for the game being played. Central to the performance of the program is the search procedure. This is a the capture tree search used in most successful janggi playing programs. It is based on the idea of using search to correct errors in evaluations of positions. This procedure is described, analyzed, tested, and implemented in the game-teaming program. Both the test results and the performance of the program confirm the results of the analysis which indicate that search improves game playing performance for sufficiently accurate evaluation functions.