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The course is organized around curated datasets that mirror real-world data science practice and supports experiential and peer learning through Kaggle. Peer learning is reinforced via a genetic-algorithm-inspired structure where students access each other’s solutions and iteratively improve week by week. Course implementation details are provided, and efficacy is evaluated with student surveys and a focus group, indicating reduced perceived gaps and achievement of learning outcomes.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/a-data-first-approach-to-learning-real-world-statistical-modeling/596223/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/a-data-first-approach-to-learning-real-world-statistical-modeling/596223.png","ImageObject",300,407,{"name":92,"@type":93},"Guten tag","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-21","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"How is the statistics course designed differently from traditional method-first courses?","Question",{"text":112,"@type":113},"The course is structured around curated datasets rather than presenting methods first and applying them to polished datasets.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What mechanism supports peer learning in the course?",{"text":117,"@type":113},"Peer learning is encouraged by giving students access to each other’s solutions, modeled after a genetic algorithm, to help them learn from prior work and improve weekly.",{"name":119,"@type":110,"acceptedAnswer":120},"How is course effectiveness assessed in the study?",{"text":121,"@type":113},"Effectiveness is assessed using a survey of students and a focus group, and responses indicate successful achievement of desired learning outcomes.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},596223,1792211512,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":46,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":31},687212321768,"https://ap-avatar.wpscdn.com/avatar/a0010bdbe886d2fe77?x-image-process=image/resize,m_fixed,w_180,h_180&k=1789897067658708522","The Canadian Journal for the Scholarship of Teaching and Learning  \n\n| Volume 13 | Issue 1 | Article 6 |\n| --- | --- |\n| Winter 02-15-2022\u003Cbr>A Data-First Approach to Learning Statistical Modeling\u003Cbr>Luke Bornn\u003Cbr>Simon Fraser University, [lbornn@sfu.ca](lbornn@sfu.ca)[ ](lbornn@sfu.ca)Jacob Mortensen\u003Cbr>Simon Fraser University, [jmortens@sfu.ca](jmortens@sfu.ca)[ ](jmortens@sfu.ca)Daria Ahrensmeier\u003Cbr>Simon Fraser University, [dahrensm@sfu.ca](dahrensm@sfu.ca)\u003Cbr>Follow this and additional works at: [https://www.cjsotl-rcacea.ca](https://www.cjsotl-rcacea.ca)\u003Cbr>[https://doi.org/10.5206/cjsotlrcacea.2022.1.10204](https://doi.org/10.5206/cjsotlrcacea.2022.1.10204) | Real-World |\n\nRecommended Citation  \nBornn, L., Mortensen, J., & Ahrensmeier, D. (2022) . A data-first approach to learning real-world statistical modeling. The Canadian Journal for the Scholarship of Teaching and Learning, 13(1) .  \n[https://doi.org/10.5206/cjsotlrcacea.2022.1.10204](https://doi.org/10.5206/cjsotlrcacea.2022.1.10204)  \nA Data-First Approach to Learning Real-World Statistical Modeling  \nAbstract  \nThis paper presents a novel design for an upper-level undergraduate statistics course structured around data rather than methods. The course is designed around curated datasets to reflect real-world data science practice and engages students in experiential and peer learning using the data science competition platform Kaggle. Peer learning is further encouraged by patterning the course after a genetic algorithm: students have access to each other’s solutions, allowing them to learn from what others have done and figure out how to improve upon previous work from week to week. Implementation details for the course are provided, and course efficacy is assessed using a survey of students and a focus group. Student responses suggest that the structure of the course contributed to narrowing the perceived gap between low- and high-performing students, that desired learning outcomes were successfully achieved, and that a data-first approach to learning statistics is effective for learning.  \nCet article présente une conception nouvelle pour un cours de statistiques de fin de premier cycle structuré autour de données plutôt que de méthodes. Le cours est conçu autour d’ensembles de données conservées qui reflètent les pratiques de la science des données du monde réel et engage les étudiants et les étudiantes dans un apprentissage basé sur l’expérience et sur l’apprentissage par les pairs en utilisant la plate-forme de compétition de science des données Kaggle. L’apprentissage par les pairs est également encouragé grâce à la modélisation du cours sur un algorithme génétique : les étudiants et les étudiantes ont accès aux solutions des uns et des autres, ce qui leur permet d’apprendre à partir de ce que les autres ont fait et de trouver comment s’améliorer par rapport à leur travail passé d’une semaine à l’autre. Les détails de la mise en oeuvre du cours sont fournis et l’efficacité du cours est évaluée grâce à un sondage auprès des étudiants et des étudiantes et à un groupe de discussion. Les réponses des étudiants et des étudiantes suggèrent que la structure du coursa contribué à réduire l’écart perçu qui existait entre les étudiants et les étudiantes les plus forts et les plus faibles, que les résultats d’apprentissage désirés avaient été atteints et que l’approche axée sur les données pour l’apprentissage des statistiques était efficace pour l’apprentissage.  \nKeywords  \nstatistics education research, data science learning, authentic assessment; recherche sur l’enseignement des statistiques, apprentissage de la science des données, évaluation authentique  \nThis research paper/Rapport de recherche is available in The Canadian Journal for the Scholarship of Teaching and Learning:  \n[https://doi.org/10.5206/cjsotlrcacea.2022.1.10204](https://doi.org/10.5206/cjsotlrcacea.2022.1.10204)  \nApplied statistics courses in post-secondary schools/undergraduate programs are f","cbCaiv2C1Uxi2UIo","https://ap.wps.com/l/cbCaiv2C1Uxi2UIo","pdf",555089,"English","# Abstract\n## Course design centered on data\n## Peer learning through Kaggle and genetic algorithm patterning\n## Implementation and efficacy assessment","[{\"question\":\"How is the statistics course designed differently from traditional method-first courses?\",\"answer\":\"The course is structured around curated datasets rather than presenting methods first and applying them to polished datasets.\"},{\"question\":\"What mechanism supports peer learning in the course?\",\"answer\":\"Peer learning is encouraged by giving students access to each other’s solutions, modeled after a genetic algorithm, to help them learn from prior work and improve weekly.\"},{\"question\":\"How is course effectiveness assessed in the study?\",\"answer\":\"Effectiveness is assessed using a survey of students and a focus group, and responses indicate successful achievement of desired learning outcomes.\"}]","A Data-First Approach to Learning Real-World Statistical Modeling | PDF",1792082673]