Elsa Medina

Bio: Elsa Medina is an academic researcher from California Polytechnic State University. The author has contributed to research in topics: Statistics education & Statistical literacy. The author has an hindex of 7, co-authored 19 publications receiving 654 citations.

Developing Students’ Statistical Reasoning: Connecting Research and Teaching Practice

Abstract: Foreword Roxy Peck Preface Joan Garfield and Dani Ben-Zvi Part I. The Foundations of Statistics Education Chapter 1 The Discipline of Statistics Education Chapter 2 The Research on Teaching and Learning Statistics Chapter 3 Creating a Statistical Reasoning Learning Environment Chapter 4 Assessment in Statistics Education Chapter 5 Using Technology to Improve Student Learning of Statistics Part II. From Research to Practice: Developing the Big Ideas of Statistics Introduction to Part II Connecting Research to Teaching Practice Chapter 6 Learning to Reason about Data Chapter 7 Learning to Reason about Statistical Models and Modeling Chapter 8 Learning to Reason about Distribution Chapter 9 Learning to Reason about Center Chapter 10 Learning to Reason about Variability Chapter 11 Learning to Reason about Comparing Groups Chapter 12 Learning to Reason about Samples and Sampling Distributions Chapter 13 Learning to Reason about Statistical Inference Chapter 14 Learning to Reason about Covariation Part III. Implementing Change through Collaboration Introduction to Part III The Role of Collaboration in Improving Statistics Education: In Learning, in Teaching, and in Research Chapter 15 Collaboration in the Statistics Classroom Chapter 16 Collaboration in Teaching and Research ReferencesResources Tables of Activities Author Index Subject Index

The Role of Technology in Improving Student Learning of Statistics

Abstract: This paper provides a broad overview of the role technological tools can play in helping students understand and reason about important statistical ideas. We summarize recent developments in the use of technology in teaching statistics in light of changes in course content, pedagogical methods, and instructional formats. Issues and practical challenges in selecting and implementing technological tools are presented discussed, and examples of exemplary tools are provided along with suggestions for their use.

Multimedia in Learning

Abstract: A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

미국 NCTM의 Principles and Standards for School Mathematics에 나타난 수학과 교수,학습의 이론

Abstract: 미국의 “전국 수학 교사 협의회”(National Council of Teachers of Mathematics, NCTM)는 1989년부터 〈학교 수학의 교육과정과 평가 규준〉(1989), 〈수학 가르침(교수)의 전문성 규준〉(1991), 〈학교 수학의 평가(시험) 규준〉(NCTM, 1995), 〈학교 수학의 원리와 규준〉(2000)을 출판하여 미국의 수학 교육 의 전망(목표, 나아갈 길)과 규준(실행 지침)을 제시하였다. 수학 교사들로 구성된 미국의 NCTM은 학생, 학부모, 학교 행정가 등 많은 사람들과 힘을 합하여 모든 학생들에게 수준 높은 수학 교육을 받을 수 있는 여건(환경, 기회)을 조성하는 데 구심점의 역할을 하였다. 한편 많은 관련 단체들은 여러 배경과 능력을 가진 학생들이 전문성을 지닌 교사(특수 교사를 일컫는 밀이 아니다. 수학 교과를 이해하고 수학의 전문성과 특수성을 가르칠 수 있는 일반 교사를 일컫는 말이다.)로부터 미래를 대비해 평등하고, 진취적이며, 지원이 잘 이루어지고, 공학 도구(IT)가 잘 갖춰진 환경에서 중요한 수학적 아이디어를 이해하면서 학습할 수 있는 수학 교실(미국에서는 우리나라처럼 수학 교사가 수학 시간에 학생의 방(교실: Homeroom)에 찾아가지 않고 학생들이 선생의 방(수학 교실: Classroom)을 찾아온다. 전형적인 수학 교실의 사진은 2쪽에 나와 있다.)을 만들기 위해 함께 힘썼다. NCTM에서 출간한 여러 규준들은 우리나라의 제6차와 제7차 교육과정에도 큰 영향을 미쳤다. 이 글에서는 NCTM(2000)에서 제시한 학습 원리를 간단히 살펴본 다음 이를 중심으로 현재 미국 수학 교육의 교수ㆍ학습 이론의 동향을 살펴본다.

How Students Learn Statistics Revisited: A Current Review of Research on Teaching and Learning Statistics

Abstract: Summary This paper provides an overview of current research on teaching and learning statistics, summarizing studies that have been conducted by researchers from different disciplines and focused on students at all levels. The review is organized by general research questions addressed, and suggests what can be learned from the results of each of these questions. The implications of the research are described in terms of eight principles for learning statistics from Garfield (1995) which are revisited in the light of results from current studies.