Introduction to the Special Issue: Highlighting AERA’s Online Teaching and Learning SIG 2020

Introduction to the Special Issue: Highlighting AERA’s Online Teaching and Learning SIG 202

Instructional Design Learners Make Sense of Theory: A Collaborative Autoethnography

Understanding theory is essential to instructional design (ID) research and practice; however, novice designers struggle to make sense of instructional design theory due to its abstract and complex nature, the inconsistent use of theoretical terms and concepts within literature, and the dissociation of theory from practice. While these challenges are generally understood, little is known about the sensemaking process of learners as they encounter these challenges in pursuit of deeper theoretical understanding. Using a collaborative autoethnographic approach, six ID learners investigated their sensemaking experience within an advanced ID theory course. Autoethnography, a form of qualitative research, focuses on self-reflection “to gain an understanding of society through the unique sense of self” (Chang et al., 2013, p. 18). Collaborative autoethnography, a type of autoethnography, explores anecdotal and personal experiences “collectively and cooperatively within a team of researchers” (p. 21). Using individual and collective reflexive and analytic activities, this inquiry illuminates the numerous sensemaking approaches ID learners commonly used to move beyond their initial, basic theoretical understanding, including deconstructing theory, distinguishing terminology, integrating concepts with previous knowledge, and maintaining an openness to multiple perspectives. Additionally, ID learners experienced significant struggles in this process but viewed these struggles as significant and motivating elements of their sensemaking process. Finally, this study offers implications for learners, instructors, and course designers

Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1-3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods - recursive partitioning and regression - to pinpoint disease susceptibility to the MHC class I genes HLA-B and HLA-A (risk ratios >1.5; Pcombined = 2.01 × 10-19 and 2.35 × 10-13, respectively) in addition to the established associations of the MHC class II genes. Other loci with smaller and/or rarer effects might also be involved, but to find these, future searches must take into account both the HLA class II and class I genes and use even larger samples. Taken together with previous studies, we conclude that MHC-class-I-mediated events, principally involving HLA-B*39, contribute to the aetiology of type 1 diabetes. ©2007 Nature Publishing Group

Instructor Leadership and the Community of Inquiry Framework: Applying Leadership Theory to Higher Education Online Learning

Higher education institutions continue to invest in online learning, yet research indicates instructors often lack experience, preparation, and guidance for teaching online. While instructor leadership is essential for meaningful online learning, few studies have investigated online instructors’ leadership behaviors. This study offers new insights into the conceptual and empirical alignment between instructor leadership, as interpreted through the dual lenses of organizational leadership theory and the Community of Inquiry (CoI) framework, proposing instructor leadership as foundational to the teaching and learning experience in a CoI. Specifically, the convergent mixed methods study investigated students’ (N = 87) and instructors’ (N = 7) perceptions of instructor servant leadership (SL) behaviors in an online graduate-level course designed to facilitate a CoI. Results demonstrate instructor SL behaviors were perceived differently by students and instructors, instructors’ self-perceptions were generally higher than students’ perceptions, and students’ perceptions of instructor SL were positively correlated with their satisfaction with the course and instructor. Implications offer insights into instructor leadership behaviors important for developing instructor leadership presence to facilitate meaningful learning and student satisfaction in higher education online learning

Instructor Leadership in Online Learning: Predictive Relationships Between Servant Leadership and the Community of Inquiry Framework

Instructor leadership is widely recognized as essential for facilitating meaningful online learning in higher education. While previous studies have applied organizational leadership theories to the study of instructor leadership, fewer studies have investigated online instructor leadership. This predictive correlational study detailed the associations between the Community of Inquiry (CoI) framework and servant leadership (SL) theory and employed multiple regression analyses to investigate the predictive relationships of seven SL dimensions on the three CoI presences. Survey data were gathered from 148 graduate students enrolled in online courses in education, communication, and engineering master’s degree programs using the CoI Survey (Arbaugh et al., 2008) and the SL-28 (Liden at al., 2008). The findings revealed a positive and highly significant correlation between the instruments. The predictive model as a whole explained 66% of the variance in students’ perceptions of a CoI. Three SL predictor variables demonstrated the most influence: helping subordinates grow and succeed, conceptual skills, and creating value for the community. Additional analyses at the CoI subscale level revealed that the SL variables accounted for 73% of the variance in teaching presence, 55% of the variance in cognitive presence, and 31% of the variance in social presence. Implications and limitations are discussed and recommendations are proposed to implement online instructor SL

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P &lt; 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research

Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases