{"id":1971,"date":"2026-08-06T12:56:14","date_gmt":"2026-08-06T12:56:14","guid":{"rendered":"https:\/\/www.ahmadinia.fi\/index.php\/portfolio\/teaching-portfolio\/"},"modified":"2026-08-11T06:52:18","modified_gmt":"2026-08-11T06:52:18","slug":"teaching-portfolio","status":"publish","type":"academic_item","link":"https:\/\/www.ahmadinia.fi\/index.php\/portfolio\/teaching-portfolio\/","title":{"rendered":"Teaching Portfolio"},"content":{"rendered":"
\n

Teaching Portfolio<\/h2>\n

A. Course development and teaching at the University of Turku<\/h3>\n

I have designed and will teach SOST0091 Data Analytics with Python for Social Sciences I<\/em>, a five-credit advanced-studies course at the University of Turku. The course runs from 3 November to 18 December 2026 and is taught in English.<\/p>\n

\n
\"Publicum
Publicum, University of Turku<\/figcaption><\/figure>\n<\/div>\n

The course provides a low-threshold introduction to quantitative data analysis for social science students. No previous Python experience is required. Students are expected to have completed bachelor-level quantitative methods or equivalent studies.<\/p>\n

The course begins with social science research questions, concepts and measurement. Students then progress through Excel, Python, data cleaning, missing-data management, descriptive statistics, visualisation, probability, hypothesis testing, reproducible analysis and an introduction to statistical learning.<\/p>\n

The course uses authentic social science and public datasets, including the European Social Survey, General Social Survey, World Development Indicators, Gapminder, World Happiness Report, Freedom House data, Statistics Finland data and other teaching datasets.<\/p>\n

My responsibilities include designing the course and its Moodle environment, preparing and delivering lectures and computer laboratories, creating slides and Jupyter Notebooks, selecting and preparing datasets, producing instructional videos, developing H5P activities and Kahoot quizzes, preparing assignments, giving feedback and supervising the data-analysis report and final mini-project.<\/p>\n

The published course workload consists of 24 lecture hours, 16 computer-laboratory hours and approximately 95 hours of independent study. Assessment is based on weekly hands-on exercises, a data-analysis report and a final mini-project. The course is assessed as Pass\/Fail.<\/p>\n

Table 1. Teaching details at the University of Turku<\/h4>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Date<\/th>\nSession topic<\/th>\nLearning goals<\/th>\nResponsibilities<\/th>\nHours<\/th>\n<\/tr>\n<\/thead>\n
03.11.2026<\/td>\nSession 1: From Social Science Questions to Data<\/td>\nRecognise different types of social science data and connect research questions with variables and evidence.<\/td>\nLecture delivery, guided discussion, paper-based dataset activity, Kahoot review and Moodle exercise.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
05.11.2026<\/td>\nSession 2: From Research Questions to Analysable Data<\/td>\nTurn broad topics into answerable research questions, measurable variables and basic codebooks.<\/td>\nLecture delivery, research-question exercises, operationalisation activities and codebook guidance.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
10.11.2026<\/td>\nSession 3: Inspecting and Summarising Social Science Data \u2014 Excel I<\/td>\nInspect datasets and calculate counts, percentages, measures of centre and measures of spread in Excel.<\/td>\nExcel demonstrations, guided formula practice, interpretation activities and exercise support.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
12.11.2026<\/td>\nSession 4: Excel II \u2014 Group Comparison, Visualisation, Lookup and Regression Preview<\/td>\nCompare groups, create PivotTables and charts, use lookup functions and interpret introductory regression output.<\/td>\nExcel demonstrations, group-comparison exercises, visualisation guidance and regression discussion.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
13.11.2026<\/td>\nSession 5: Computer Lab I \u2014 Opening, Inspecting and Cleaning ESS Survey Data<\/td>\nOpen data files, inspect variables and codes, clean missing values, recode variables and save analysis-ready data.<\/td>\nComputer-laboratory supervision, pandas demonstrations, troubleshooting and notebook feedback.<\/td>\n3 laboratory hours<\/td>\n<\/tr>\n
17.11.2026<\/td>\nSession 6: Python I \u2014 Cleaning and Reshaping WDI Macro Data<\/td>\nRemove non-data rows, rename columns, reshape data from wide to long format and produce summaries.<\/td>\nPython demonstrations, coding exercises, data-preparation guidance and notebook support.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
19.11.2026<\/td>\nSession 7: Python II \u2014 Missing Data and Analysis-Ready GSS Records<\/td>\nDetect labelled missing values, replace them correctly, convert variables and document cleaning decisions.<\/td>\nTeaching missing-data principles, coding demonstrations, exercises and feedback.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
20.11.2026<\/td>\nSession 8: Computer Lab II \u2014 Reproducibility, Debugging and Gapminder<\/td>\nStructure a readable notebook, check data quality, debug errors, save outputs and run a complete analysis reproducibly.<\/td>\nLaboratory supervision, debugging support, reproducibility checks and notebook review.<\/td>\n3 laboratory hours<\/td>\n<\/tr>\n
24.11.2026<\/td>\nSession 9: Descriptive Statistics and Exploratory Data Analysis<\/td>\nCalculate and interpret centre, spread, frequencies, percentages, group comparisons, cross-tabulations and correlations.<\/td>\nStatistical explanation, Python demonstrations, interpretation exercises and coding support.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
26.11.2026<\/td>\nSession 10: Python Visualisation \u2014 Honest, Accessible Social Science Charts<\/td>\nCreate appropriate distribution, group-comparison and relationship charts and apply accessible design principles.<\/td>\nVisualisation teaching, chart demonstrations, design review and feedback on student-created figures.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
27.11.2026<\/td>\nSession 11: Computer Lab III \u2014 A Mini Visual EDA Report<\/td>\nConnect a focused research question with data cleaning, a descriptive table, visualisations and limitations.<\/td>\nLaboratory supervision, report development, chart review and written-interpretation feedback.<\/td>\n3 laboratory hours<\/td>\n<\/tr>\n
01.12.2026<\/td>\nSession 12: Probability and Variability<\/td>\nUnderstand observed probabilities, expected values, variance, standard deviation, z-scores, sampling variability and intervals.<\/td>\nExplanation of probability concepts, Python simulations, guided exercises and interpretation support.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
03.12.2026<\/td>\nSession 13: Hypothesis Testing with Descriptives First<\/td>\nConduct and interpret Welch\u2019s t-test, chi-square tests and ANOVA, calculate effect sizes and check assumptions.<\/td>\nStatistical teaching, test demonstrations, diagnostic guidance and reporting exercises.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
04.12.2026<\/td>\nSession 14: Full Analysis Pipeline \u2014 From Raw Table to Mini-Project Draft<\/td>\nComplete an analysis from a research question and raw data to cleaning, tables, visualisations, comparisons and limitations.<\/td>\nFull-day laboratory teaching, individual troubleshooting, analysis guidance and mini-project support.<\/td>\n7 laboratory hours<\/td>\n<\/tr>\n
08.12.2026<\/td>\nSession 15: Statistical-Learning Bridge<\/td>\nDistinguish targets from predictors, understand training and test data and interpret a simple predictive model cautiously.<\/td>\nGuided model demonstration, evaluation exercises and discussion of limitations.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n
10.12.2026<\/td>\nSession 16: Review and Consolidation \u2014 Repair the Workflow<\/td>\nDiagnose and repair inconsistent variable names, mixed types, missing values and duplicates.<\/td>\nCourse review, debugging workshop, individual feedback and mini-project preparation.<\/td>\n2 lecture hours<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

Final assessment session<\/h4>\n
\n\n\n\n\n\n
Date<\/th>\nActivity<\/th>\nPurpose<\/th>\nResponsibilities<\/th>\nHours<\/th>\n<\/tr>\n<\/thead>\n
18.12.2026<\/td>\nFinal mini-project and course assessment<\/td>\nDemonstrate a correct, reproducible and clearly reported social science data analysis.<\/td>\nFinal guidance, assessment, feedback and course completion.<\/td>\n4 hours<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

B. Teaching experience at Metropolia University of Applied Sciences<\/h3>\n
\n
\"Metropolia
Metropolia University of Applied Sciences<\/figcaption><\/figure>\n<\/div>\n

As part of my pedagogical training in the International Professional Teacher Education programme at H\u00e4me University of Applied Sciences, I taught Data Analytics & Statistics in Python<\/em> at Metropolia University of Applied Sciences.<\/p>\n

The three-credit course was offered through the Information Technology programme for Bachelor\u2019s and Master\u2019s students in Engineering. It developed practical skills in data analytics, statistical modelling and data visualisation using Python.<\/p>\n

The curriculum covered data manipulation with pandas and NumPy, descriptive and inferential statistics, probability distributions, regression, correlation, time-series forecasting and predictive analytics. A specialised section introduced cryptocurrency data analytics to connect statistical methods with a practical application.<\/p>\n

My responsibilities included designing and delivering online lectures, creating coding exercises and assignments, assessing student progress and supervising final mini-projects. The course followed an interactive, project-based approach in which students applied methods to real datasets.<\/p>\n

Table 2. Teaching details at Metropolia University of Applied Sciences<\/h4>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n
Date<\/th>\nSession topic<\/th>\nLearning goals<\/th>\nResponsibilities<\/th>\nHours<\/th>\n<\/tr>\n<\/thead>\n
05.03.2025<\/td>\nPython recap<\/td>\nReview basic Python concepts and syntax.<\/td>\nLecture delivery, hands-on coding exercises and guided discussion.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
12.03.2025<\/td>\nMatrices and data frames<\/td>\nManipulate data using NumPy and pandas.<\/td>\nLecture delivery, coding exercises and troubleshooting.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
19.03.2025<\/td>\nStatistics: theory and application<\/td>\nUnderstand key statistical measures.<\/td>\nExplanation of statistical concepts and facilitation of practical exercises.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
26.03.2025<\/td>\nProbability and variability<\/td>\nUnderstand probability distributions and significance tests.<\/td>\nTeaching probability concepts and guiding probability-based coding exercises.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
02.04.2025<\/td>\nRelationships between variables<\/td>\nExplore regression and correlation.<\/td>\nExplanation of regression models and guidance in correlation analysis.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
09.04.2025<\/td>\nData visualisation<\/td>\nCreate effective visualisations with Matplotlib and seaborn.<\/td>\nTeaching visualisation techniques and reviewing student-created charts.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
16.04.2025<\/td>\nAdvanced topics and integration<\/td>\nApply several analytical methods to practical problems.<\/td>\nExplaining integrated analytical workflows and guiding exploratory analysis.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n
23.04.2025<\/td>\nStudent mini-project presentations<\/td>\nPresent and discuss projects that demonstrate learning.<\/td>\nProviding feedback, evaluating final projects and grading presentations.<\/td>\n2 teaching hours + 15 planning and supervision hours<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

C. Teaching experience at \u00c5bo Akademi University<\/h3>\n

During my doctoral studies in the Faculty of Social Sciences, Business and Economics, and Law at \u00c5bo Akademi University, I contributed to teaching in information studies.<\/p>\n

\"ASA
ASA Library, \u00c5bo Akademi University<\/figcaption><\/figure>\n

I created and delivered modules for the international Master\u2019s programme in Governance of Digitalisation, particularly within Information Behaviour I<\/em> and Information Behaviour II<\/em>.<\/p>\n

In autumn 2022, I taught the Applications of Literacies module in Information Behaviour I. The module focused on information literacy, digital literacy and the role of digital skills in personal, academic and professional life.<\/p>\n

During the spring terms of 2022, 2023 and 2024, I taught a section of Information Behaviour II on health information behaviour. The teaching covered health-information-seeking behaviour, personal and contextual influences on information practices and the Health Belief Model. These sessions were informed by my doctoral research.<\/p>\n

Table 3. Teaching details at \u00c5bo Akademi University<\/h4>\n
\n\n\n\n\n\n\n\n\n
Academic year<\/th>\nCourse<\/th>\nModule taught<\/th>\nResponsibilities<\/th>\nHours<\/th>\n<\/tr>\n<\/thead>\n
Spring 2024<\/td>\nInformation Behaviour II<\/td>\nHealth Information Behaviour<\/td>\nPreparing and recording lectures, facilitating group assignments and learning diaries, and grading activities.<\/td>\n1 teaching hour + 15 supervision hours<\/td>\n<\/tr>\n
Spring 2023<\/td>\nInformation Behaviour II<\/td>\nHealth Information Behaviour<\/td>\nPreparing and recording lectures, facilitating group assignments and learning diaries, and grading activities.<\/td>\n1 teaching hour + 15 supervision hours<\/td>\n<\/tr>\n
Autumn 2022<\/td>\nInformation Behaviour I<\/td>\nApplications of Literacies<\/td>\nPreparing and recording lectures, facilitating group assignments and learning diaries, and grading activities.<\/td>\n1 teaching hour + 15 supervision hours<\/td>\n<\/tr>\n
Spring 2022<\/td>\nInformation Behaviour II<\/td>\nHealth Information Behaviour<\/td>\nPreparing and recording lectures, facilitating group assignments and learning diaries, and grading activities.<\/td>\n1 teaching hour + 15 supervision hours<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

D. Teaching experience at Islamic Azad University<\/h3>\n

From 2011 to 2014, I worked as a lecturer and researcher at Islamic Azad University before moving to Finland to complete my second Master\u2019s degree and doctorate.<\/p>\n

\"Islamic
Islamic Azad University<\/figcaption><\/figure>\n

I taught students at associate-degree and Bachelor\u2019s levels in finance, taxation, accounting, investment, financial projects and computer applications in accounting.<\/p>\n

My teaching combined clear explanations, practical examples, structured exercises, group assignments, case analysis, written examinations and applied projects. I used everyday financial decisions and business situations to help students understand abstract concepts.<\/p>\n

Table 4. Teaching details at Islamic Azad University<\/h4>\n
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Course<\/th>\nSemester \/ year<\/th>\nCode<\/th>\nLevel<\/th>\nType<\/th>\nCredits<\/th>\nHours per semester<\/th>\n<\/tr>\n<\/thead>\n
Investing in the Stock Exchange<\/td>\nSummer 2012\u20132013<\/td>\n718<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Finance 2<\/td>\nSummer 2012\u20132013<\/td>\n1309<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n3<\/td>\n48<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nSecond semester 2012\u20132013<\/td>\n4092<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nSecond semester 2012\u20132013<\/td>\n4091<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nSecond semester 2012\u20132013<\/td>\n4094<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Finance Class<\/td>\nSecond semester 2010\u20132011<\/td>\n7356<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n3<\/td>\n48<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nSecond semester 2010\u20132011<\/td>\n10307<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nSecond semester 2010\u20132011<\/td>\n7085<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2013\u20132014<\/td>\n1603<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2013\u20132014<\/td>\n1604<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2013\u20132014<\/td>\n3827<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2013\u20132014<\/td>\n3829<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2013\u20132014<\/td>\n3832<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Finance 1<\/td>\nFirst semester 2011\u20132012<\/td>\n4883<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n3<\/td>\n48<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2011\u20132012<\/td>\n11502<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2011\u20132012<\/td>\n11505<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Computer Application in Accounting \u2013 2<\/td>\nFirst semester 2011\u20132012<\/td>\n11511<\/td>\nBachelor\u2019s<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2011\u20132012<\/td>\n3793<\/td>\nAssociate degree<\/td>\nCore\/elective<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n
Tax Accounting<\/td>\nFirst semester 2011\u20132012<\/td>\n3788<\/td>\nBachelor\u2019s<\/td>\nCore<\/td>\n2<\/td>\n32<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Course development and documented teaching across the University of Turku, Metropolia University of Applied Sciences, \u00c5bo Akademi University and Islamic Azad University.<\/p>\n","protected":false},"author":1,"featured_media":2625,"comment_status":"open","ping_status":"closed","template":"","meta":{"had_date":"2026-01-01","had_date_precision":"year","had_venue":"University of Turku \u00b7 Metropolia \u00b7 \u00c5bo Akademi \u00b7 Islamic Azad University","had_authors":"Hamed Ahmadinia \u00b7 Teaching portfolio","had_external_url":"","had_doi":"","had_citation":"","had_meta_label":"Teaching portfolio","had_amount":"Four institutions","had_location":"","had_topic":"","had_field":"","had_method":"","had_data_source":"","had_participants":"","had_platform":"Teaching Portfolio and Pedagogical Practice","had_level":"Institutional teaching record","had_publisher":"","had_language":"English","had_jufo":"","had_institution":"University of Turku \u00b7 Metropolia \u00b7 \u00c5bo Akademi \u00b7 Islamic Azad University","had_students":"","had_credits":"","had_format":"Teaching Portfolio","had_city":"","had_latitude":"","had_longitude":"","had_quantity":"","had_amount_eur":"","had_currency":"","had_country":"","had_project_id":"","had_teaching_portfolio_role":"portfolio","had_featured":false,"had_news_effect":"global","had_abstract":"","had_keywords":"","had_isbn":"","had_issn":"","had_volume":"","had_issue":"","had_pages":"","had_publication_place":"","had_edition":"","had_project_ids":"","footnotes":"","_had_popup_image_id":2625,"_had_popup_image_fit":"automatic"},"tags":[340,156,157,343,338,337,336,351],"academic_type":[],"class_list":["post-1971","academic_item","type-academic_item","status-publish","has-post-thumbnail","hentry","tag-abo-akademi","tag-assessment","tag-course-design","tag-islamic-azad-university","tag-metropolia","tag-supervision","tag-teaching-experience","tag-university-of-turku"],"_links":{"self":[{"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/academic_item\/1971","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/academic_item"}],"about":[{"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/types\/academic_item"}],"author":[{"embeddable":true,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/comments?post=1971"}],"version-history":[{"count":11,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/academic_item\/1971\/revisions"}],"predecessor-version":[{"id":3063,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/academic_item\/1971\/revisions\/3063"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/media\/2625"}],"wp:attachment":[{"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/media?parent=1971"}],"wp:term":[{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/tags?post=1971"},{"taxonomy":"academic_type","embeddable":true,"href":"https:\/\/www.ahmadinia.fi\/index.php\/wp-json\/wp\/v2\/academic_type?post=1971"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}