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Daeun Choi,Youngmi Lee,Haeryun Park,Kyunghee Song,Jinah Hwang 한국영양학회 2021 Nutrition Research and Practice Vol.15 No.2
BACKGROUND/OBJECTIVES: This study analyzed the quality of lunches provided in senior leisure service (SLS) facilities and compared institutional foodservice (IF) and noninstitutional foodservice (non-IF). SUBJECTS/METHODS: Data of 390 adults aged 65 years or older who ate lunches in SLS facilities were analyzed using the information from the 2013–2017 Korea National Health and Nutrition Examination Survey. The participants were classified into IF (n = 129) and non-IF (n = 261) groups according to meal type provided. The intake of major food groups, energy and nutrients, and nutrient adequacy ratio (NAR) and mean adequacy ratio (MAR) were analyzed. The diversity of meals was evaluated by food group patterns, dietary diversity score (DDS) and dietary variety score (DVS). Energy intake was adjusted in model 1, while energy and sex were adjusted in model 2. All confounding variables were adjusted in model 3. RESULTS: The intake of seafoods (P < 0.001 in models 1, 2, and 3), seaweeds (P < 0.01 in models 1 and 2), and dairy products (P < 0.05 in models 1, 2, and 3) was significantly higher in the IF group. No significant difference existed in energy intake; however, the intake of all nutrients except carbohydrate and vitamin C was significantly higher in the IF group. NAR of all nutrients, excluding vitamin C, was higher in the IF group, and MAR was also higher in the IF group (P < 0.001 in models 1, 2, and 3). The IF group had significantly higher DDS and DVS than the non-IF group (P < 0.001). CONCLUSIONS: The lunches provided in SLS facilities were better in terms of quantity and quality when provided through IF than through non-IF. More systematic foodservice programs should be implemented in SLS facilities, especially in facilities wherein users prepare their own meals.
코퍼스 – 실험 – 딥러닝 연구방법론 비교분석: ‘-도록’ 통제 구문을 중심으로
강다은(Daeun Kang),송상헌(Sanghoun Song) 한국중원언어학회 2022 언어학연구 Vol.- No.62
This study aims to examine how convergent results are showing on specific language phenomenon, by using methodological pluralism. Focusing on the ‘-tolok’ control construction, we compared the results of three research methodologies: corpus, experiment, deep learning. Previous studies used corpus exploration and language experiment separately or deep learning based on English data. However, it was not sufficiently implemented that comprehensively examining the three methodologies and deep learning analysis using large amount of data based on specific Korean language phenomenon. Accordingly, we demonstrated whether the results of quantitative analysis agree with each other for the ‘-tolok’ control construction using methodological pluralism. Furthermore, the types of Korean ‘control verb’ are classified into two types. This study is significant in showing that different types of methodology can be complement to each other by adding deep learning to the corpus and experimental methods. Additionally, we empirically revealed the necessity of revisiting the using ‘seltukha-’ as a control verb in Korean and presented four verbs that require further study to be classified as control verb, including ‘seltukha-’.
생성형 AI(Generative AI) 활용 학습 효과 메타분석
백다은 ( Daeun Baek ),손완상 ( Wansang Son ),송지훈 ( Ji Hoon Song ),유명현 ( Myunghyun Yoo ) 한국교육정보미디어학회 2024 교육정보미디어연구 Vol.30 No.4
본 연구는 국내에서 수행된 생성형 AI 활용 학습의 효과를 체계적이고 종합적으로 검토하고, 교육 분야 생성형 AI 활용을 위한 제언을 하고자 체계적 문헌 고찰과 메타분석을 실시하였다. PRISMA의 메타분석 가이드라인에 따라 최종 24편의 문헌을 분석 대상으로 선정하였으며, 생성형 AI 활용 학습과 관련된 사전/사후, 통제/처치, 상관분석 연구로 구분하여 효과 크기 산출을 위한 코딩을 진행하였다. 연구 결과, 사전/사후 연구의 경우 무선 효과모형에서 효과 크기가 0.7646으로 중간 이상의 효과 크기를 보이는 것으로 나타났다. 통제/처치 설계 연구의 경우, 고정 효과모형에서 0.4262의 중간 정도의 효과 크기를 확인하였으며, 상관관계 연구의 경우 무선 효과모형에서 전체 효과 크기가 0.5417로 중간정도의 효과 크기를 확인하였다. 사전/사후 설계 연구의 경우 생성형 AI 유형 및 학습자 유형과 같은 조절 변인에 따라 세부 효과 크기를 추가적으로 확인하였다. 그 결과, 생성형 AI 유형(텍스트 기반, 복합 생성)에 따라 텍스트 기반 생성(0.5859)에서 보다 이미지 등을 복합적으로 생성하는 경우에 더 큰 학습 효과(0.8627)를 보였다. 다음으로 학습자 유형(학령기, 성인기)에 따라서는 학령기(0.6400)보다 성인기(1.0265)에서 더 큰 학습 효과를 보였다. 이를 토대로 본 연구 결과 국내에서 수행된 생성형 AI 활용 학습의 효과를 체계적으로 검증하였으며, 향후 생성형 AI의 교육적 활용을 위한 근거 기반 실천(Evidence-based practice)을 제공하고, AI 활용 교육의 방향성을 설정하기 위한 기초자료와 시사점을 제공할 수 있다. This study conducted a systematic literature review and meta-analysis to comprehensively examine the effectiveness of learning using generative AI in South Korea and provide recommendations for its application in education. Following the PRISMA meta-analysis guidelines, 24 studies were selected for analysis. These were categorized into pre/post, control/treatment, and correlational studies, and coded for effect size calculation. Results showed that in pre/post studies, the random effects model yielded an effect size of 0.7646, indicating a medium to large effect. For control/treatment studies, a fixed effects model revealed a medium effect size of 0.4262. Correlational studies showed a medium effect size of 0.5417 in the random effects model. In pre/post design studies, additional effect sizes were examined for moderating variables such as generative AI type and learner type. Results indicated that complex generation (including images) showed greater learning effectiveness (0.8627) compared to text-based generation (0.5859). Regarding learner type, adults (1.0265) showed greater learning effectiveness than school-age learners (0.6400). This study systematically verified the effectiveness of learning using generative AI in South Korea, providing evidence-based practices for future educational applications of generative AI and offering foundational data and implications for setting directions in AI-enhanced education.