{"title":"Assessing Practical Accessibility in Online Courses Based on Local Conditions","authors":"","doi":"10.4018/978-1-5225-7528-3.ch016","DOIUrl":"https://doi.org/10.4018/978-1-5225-7528-3.ch016","url":null,"abstract":"Another approach to exploring online learning data is to see what is not there or what is absent. One use case for this is “practical accessibility” or the accessibility accommodations in online learning courses (or learning objects). This chapter includes a review of the current extant literature, a close-in analysis of several dozen real-world courses (in static format) through an instructional design/developer lens, in service of the following objectives: 1) the drafting of an initial instrument that may be used to assess the accessibility level of an online learning course or digital learning object, 2) the identification of the most common accessibility issues in online courses at a Midwestern university (based on a sample setoff online courses), and 3) the identification of a model course with full or near-full accessibility and seeing what may be learned from that and from specific accessibility accommodations that may be beneficial in other contexts.","PeriodicalId":332480,"journal":{"name":"Methods for Analyzing and Leveraging Online Learning Data","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127024485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Exploring the Common Structures and Sequences of Real-World Online Learning Modules","authors":"","doi":"10.4018/978-1-5225-7528-3.ch003","DOIUrl":"https://doi.org/10.4018/978-1-5225-7528-3.ch003","url":null,"abstract":"Online learning “modules” are generally defined as units of learning, often in reference to the amount of time that learners spend to consume the materials, acquire the learning, and test out of that sequence. No widely accepted or formal definition of such modules exist. How modules instantiate depends on many factors, not least of which is technology (authoring tools, learning management systems, and others). Given the wide availability of “modules” on open-source sharing sites, digital learning object repositories and referatories, proprietary learning management system (LMS) instances, massive open online course (MOOC) sites, cloud-based survey suites, websites, wikis, commercial proprietary online training sites, taking a bottom-up coding approach from real-world examples (both open-source and proprietary) is a healthy place to start exploring some common structures of real-world online learning modules. This chapter defines a pared-down approach to mapping online learning modules on some relevant dimensions.","PeriodicalId":332480,"journal":{"name":"Methods for Analyzing and Leveraging Online Learning Data","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122569636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Using Social Image Sets to Explore Virtual Embodiment in Second Life® as Indicators of Formal, Nonformal, and Informal Learning","authors":"","doi":"10.4018/978-1-5225-7528-3.ch007","DOIUrl":"https://doi.org/10.4018/978-1-5225-7528-3.ch007","url":null,"abstract":"Capturing Second Life® imagery sets from Yahoo's Flickr and Google Images enables indirect and backwards analysis (in a decontextualized way) to better understand the role of SL in people's virtual self-identities and online practices. Through manual bottom-up coding, based on grounded theory, such analyses can provide empirical-based understandings of how people are using SL for formal, nonformal, and informal learning. This chapter involves a review of the literature and then a light and iterated analysis of 1,550 randomly batch-downloaded screenshots from SL (including stills from machinima) to explore the potential of social image analysis to make inferences about human learning in SL in the present.","PeriodicalId":332480,"journal":{"name":"Methods for Analyzing and Leveraging Online Learning Data","volume":"138 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128763802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}