Prof.
Ernest Ampadu
Ernest Ampadu is an Associate Professor in Mathematics Education at the Department of Learning, School of Industrial Engineering and Management, at KTH Royal Institute of Technology in Sweden. Before joining KTH, Ernest worked as a senior lecturer and Head of Department, the Department of Teacher Education, University of Ghana. He also worked at the Richmond International University in London as an Assistant Professor of Mathematics and as a lecturer of mathematics and mathematics education at Anglia Ruskin University. He holds a Bachelor’s degree in Mathematics Education from the University of Cape Coast, Ghana, Research Master’s Degree in International and Comparative Education from Stockholm University, Sweden, a Master of Arts degree in Adult Learning and Global Change from Linkoping University, Sweden and a PhD in Education (Mathematics) from Anglia Ruskin University, United Kingdom.
Ernest’s principal research interests lie in the field of Mathematics Education (curriculum development, assessment, pedagogy and policy) and teacher development. He has over 20 years’ experience as a teacher educator and a researcher with in-depth experience in conducting quantitative and qualitative research. He has in-depth experience working with SPSS, STATS DIRECT and ORIGIN for statistical analysis on small and large scale projects. Ernest has participated in various international research projects outside of the university environment and has published several articles in peer-review journals and a number of book chapters.
The need for practitioners with an in-depth understanding of how to design, conduct research, collect and interpret data has become paramount in our quest for understanding the numerous challenges and dynamics in the world. This, therefore, calls for practitioners who are creative thinkers, reflective practitioners and problem solvers with an in-depth understanding of the different research designs, data collection and analysis procedures. Practitioners are involved in the collection of data on daily basis and such data sets are critical for both professional development and improving practice. The analysis and interpretation of data by practitioners in every field are critical but most practitioners may not be interested in taking a pure statistics course. The desire for this course has been necessitated by the instructor’s interaction with different practitioners (e.g., teachers, epidemiologists etc.) who argue that they have a lot of data that they think if they can analyze will go a long way in supporting their professional development and practice.
This practical course aims to introduce participants to the knowledge of basic statistical concepts and their application in the field. In addition to this, the course is aimed at introducing participants to common statistical analyses used in different fields and helping participants to develop the skills needed to conduct analyses and interpret results using descriptive statistical analysis tools. Topics to be treated include; type of data (dichotomous, continuous, nominal, categorical, ordinal, etc.); proportions, ratios and rates; building, cleaning and administering databases (including defining, computing, selecting and recoding variables for data analyses); measures of central tendency (mean, median, mode); measures of dispersion (range, extreme values, percentiles, variance, standard deviation); data presentation (tabulations, bar/pie graphs, boxplots, scatterplots, etc.); prevalence and incidence (cumulative and density).
By the end of the course, the student will be able to:
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