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This book focuses on developing methods for constructing learning paths in terms of \"learning resources\" (learning contents), \"learning approaches\" (learning method), and \"learning quality\" (learning performance) to support learning. This book defines different teaching approaches for learning activities and organizes them into a learning path which indicates the learning sequence. This book introduces how to automatically generate well-structured learning resources for different students. Also, this book introduces a method about how to generate adaptive learning approach to learn learning resources for different students. Finally, this book introduces a method to monitor and control learning quality. The adaptive learning path expresses well-structured learning contents, using which approach to access those learning contents, and in which sequence to carry out the learning process. The learning path comes with a monitoring tool to control the learning progress, which helps to make students having a balanced development on different knowledge and abilities.

Online Teaching: Tools and Techniques to Achieve Success with Learners will provide the online teacher with essential strategies to successfully design, develop, deliver and improve their online course offerings. This book is an invaluable resource for the novice instructor, as well as the seasoned educator. The chapters of the book will take the reader from the basics of online course development and delivery to assessment and improvement after a successful semester. The authors provide proven techniques, practical tools, and real-world tips in the areas of online course formats, course organization, learning management, learning community, online collaboration, learner support, visual design, course assessment, and course analysis for improvement in a readable and engaging way.

Recruitment to population-based health studies remains challenging, with difficulties meeting target participant numbers, biosample returns, and achieving a representative sample. Few studies provide evaluations of traditional and web-based recruitment methods particularly for studies with broad inclusion criteria and extended recruitment periods. Generation Scotland (GS) is a family-based cohort study that initiated a new wave of recruitment in 2022 using web-based data collection and remote saliva sampling (for genotyping). Here, we provide an overview of recruitment strategies used by GS over the first 18 months of new recruitment, highlighting which proved most effective and cost-efficient in order to inform future research. This study evaluated recruitment strategies using four main outcomes: (1) absolute recruitment numbers, (2) sociodemographic representativeness, (3) biosample return rate, and (4) cost per participant. Between May 2022 and December 2023, recruitment was undertaken via snowball recruitment (through friends and family of existing volunteers), invitations to those who participated in a previous survey (CovidLife: the GS COVID-19 impact survey), and Scotland-wide recruitment through social media (including sponsored Meta-advertisements), news media, and TV advertisement. The method of recruitment was self-reported in the baseline questionnaire. We present absolute recruitment numbers and sociodemographic characteristics by recruitment method and evaluate the saliva sample return rate by recruitment strategy using chi-square tests. The overall cost and cost per participant were calculated for each method. In total, 7889 new participants joined the cohort over this period. Recruitment sources by contribution were social media (n=2436, 30.9%), survey responder invitations (n=2049, 26.0%), TV advertising (n=367, 17.3%), snowball (n=891, 11.3%), news media (n=747, 9.5%), and other methods or unknown (n=399, 5.0%). More females signed up than males (5570/7889, 70.5% female). To date, 83.5% (6543/7836) of participants returned their postal saliva sample, which also varied by demographic factors (3485/3851, 90.5% older than 60 years vs 471/662, 71.1% aged 16-34 years). Average cost per participant across all recruitment strategies was £13.52 (US $16.82). Previous survey recontacting was the most cost-effective (£0.37 [US $0.46]), followed by social media (£14.78 [US $18.39]), while TV advertisement recruitment was the most expensive per recruit (£33.67 [US $41.89]). This study highlights both the challenges and the opportunities in large web-based cohort recruitment. Overall, social media advertising has been the most cost-effective and easily sustained strategy for recruitment over the reported recruitment period. We note that different strategies resulted in successful recruitment over varying timescales (eg, consistent sustained recruitment for social media and large spikes for news media and TV advertising), which may be informative for future studies with different requirements of recruitment periods. Limitations include self-reported methods of recruitment and difficulties in evaluating multilayered recruitment. Overall, these data demonstrate the potential cost requirements and effectiveness of different strategies that could be applied to future research studies.

The Internet is widely used to conduct research studies on health issues. Many different methods are used to recruit participants for such studies, but little is known about how various recruitment methods compare in terms of efficiency and costs. The aim of our study was to compare online and offline recruitment methods for Internet-based studies in terms of efficiency (number of recruited participants) and costs per participant. We employed several online and offline recruitment methods to enroll 18- to 45-year-old women in an Internet-based Danish prospective cohort study on fertility. Offline methods included press releases, posters, and flyers. Online methods comprised advertisements placed on five different websites, including Facebook and Netdoktor.dk. We defined seven categories of mutually exclusive recruitment methods and used electronic tracking via unique Uniform Resource Locator (URL) and self-reported data to identify the recruitment method for each participant. For each method, we calculated the average cost per participant and efficiency, that is, the total number of recruited participants. We recruited 8252 study participants. Of these, 534 were excluded as they could not be assigned to a specific recruitment method. The final study population included 7724 participants, of whom 803 (10.4%) were recruited by offline methods, 3985 (51.6%) by online methods, 2382 (30.8%) by online methods not initiated by us, and 554 (7.2%) by other methods. Overall, the average cost per participant was €6.22 for online methods initiated by us versus €9.06 for offline methods. Costs per participant ranged from €2.74 to €105.53 for online methods and from €0 to €67.50 for offline methods. Lowest average costs per participant were for those recruited from Netdoktor.dk (€2.99) and from Facebook (€3.44). In our Internet-based cohort study, online recruitment methods were superior to offline methods in terms of efficiency (total number of participants enrolled). The average cost per recruited participant was also lower for online than for offline methods, although costs varied greatly among both online and offline recruitment methods. We observed a decrease in the efficiency of some online recruitment methods over time, suggesting that it may be optimal to adopt multiple online methods.

History and social sciences educators have been charged with ensuring that our students are quantitatively literate. The internet contains a treasure trove of valid and reliable sources of quantitative data that history and social sciences teachers can easily use to satisfy the quantitative literacy requirements of the National Common Core Standards. This book contains lesson ideas, websites, numerical critical thinking questions to incorporate numerical literacy skills into class activities and assignments. Also contains lists of best practices and examples for interpreting, visualizing, and displaying quantitative data.

Evaluating digital interventions using remote methods enables the recruitment of large numbers of participants relatively conveniently and cheaply compared with in-person methods. However, conducting research remotely based on participant self-report with little verification is open to automated \"bots\" and participant deception. This paper uses a case study of a remotely conducted trial of an alcohol reduction app to highlight and discuss (1) the issues with participant deception affecting remote research trials with financial compensation; and (2) the importance of rigorous data management to detect and address these issues. We recruited participants on the internet from July 2020 to March 2022 for a randomized controlled trial (n=5602) evaluating the effectiveness of an alcohol reduction app, Drink Less. Follow-up occurred at 3 time points, with financial compensation offered (up to £36 [US $39.23]). Address authentication and telephone verification were used to detect 2 kinds of deception: \"bots,\" that is, automated responses generated in clusters; and manual participant deception, that is, participants providing false information. Of the 1142 participants who enrolled in the first 2 months of recruitment, 75.6% (n=863) of them were identified as bots during data screening. As a result, a CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Humans Apart) was added, and after this, no more bots were identified. Manual participant deception occurred throughout the study. Of the 5956 participants (excluding bots) who enrolled in the study, 298 (5%) were identified as false participants. The extent of this decreased from 110 in November 2020, to a negligible level by February 2022 including a number of months with 0. The decline occurred after we added further screening questions such as attention checks, removed the prominence of financial compensation from social media advertising, and added an additional requirement to provide a mobile phone number for identity verification. Data management protocols are necessary to detect automated bots and manual participant deception in remotely conducted trials. Bots and manual deception can be minimized by adding a CAPTCHA, attention checks, a requirement to provide a phone number for identity verification, and not prominently advertising financial compensation on social media. ISRCTN Number ISRCTN64052601; https://doi.org/10.1186/ISRCTN64052601.

Background: With the COVID-19 vaccination taking stride all across the globe, there are multiple reports of vaccine-induced adverse reactions (cutaneous and systemic). Objectives: To study the frequency and characteristics of mucocutaneous reactions to COVID-19 vaccines. Methods: An online questionnaire-based study was performed among the recipients of COVID-19 vaccines Results: Majority (73.6%) of the responders had received the Covishield vaccine (AstraZeneca-Oxford), while 26.4% had been vaccinated with Covaxin (Bharat Biotech-ICMR). One or more post-vaccination mucocutaneous effects were experienced in 87 (19.6%) participants. Vaccine-associated mucocutaneous changes were observed in 19.7% and 22.2% of individuals who received Covishield and Covaxin, respectively. Local injection site reaction was the predominant mucocutaneous finding, followed by urticarial rash, exacerbation of preexisting dermatoses, morbilliform rash, apthous ulcers, pityriasis rosea like eruption, telogen effluvium, herpes zoster, purpuric rash, erythema multiforme and others. Anaphylaxis was reported in three individuals. However, fatality was not reported in any of the vaccine recipients. Intergroup assessment of parameters with respect to type of vaccine was found to be insignificant. Conclusion: Majority reported mild and self-limiting reactions. This outcome should not discourage the common man in getting vaccinated.