Developing a new generation MOOC (ngMOOC): a design-based implementation research project with cognitive architecture and student feedback in mind

This paper describes a design-based implementation research (DBIR) approach to the development and trialling of a new generation massive open online course (ngMOOC) situated in an instructional setting of undergraduate mathematics at a regional Australian university. This process is underscored by two important innovations: (a) a basis in a well-established human cognitive architecture in terms of cognitive load theory; and (b) point-of-contact feedback based in a well-tested online system dedicated to enhancing the learning process. Analysis of preliminary trials suggests that the DBIR approach to the ngMOOC construction and development supports theoretical standpoints that argue for an understanding of how design for optimal learning can utilise conditions, such as differing online or blended educational contexts, in order to be effective and scalable. The ngMOOC development described in this paper marks the adoption of a cognitive architecture in conjunction with feedback systems, offering the groundwork for use of adaptive systems that cater for learner expertise. This approach seems especially useful in constructing and developing online learning that is self-paced and curriculum-based

Clear-cell carcinoma of the breast, resembling clear-cell carcinoma of the kidney

The lobular arrangement and the fine vascular network are clearly visible.<p><b>Copyright information:</b></p><p>Taken from "Glycogen-rich clear cell carcinoma of the breast"</p><p>http://www.wjso.com/content/6/1/44</p><p>World Journal of Surgical Oncology 2008;6():44-44.</p><p>Published online 29 Apr 2008</p><p>PMCID:PMC2386120.</p><p></p

Comparison of CTLA-4 genotype relationship profiles of five most case-control discriminating <i>RRP</i>'s.

<p><b><i>RRP₂</i></b> (dashed edges) is shown in both panels for reference. Symbols as in Fig. 1.</p

Case-control discrimination by “missing” CTLA-4 genotype reference profile <i>rrp₈</i> (dashed lines in all figures).

<p>Solid lines in schemes <b>a</b>) – <b>e</b>) show five <b><i>prp</i></b> CTLA-4 genotype profiles, found exclusively for 219 (77%) patients identified from the complete case cohort by condition that their <b><i>prp</i></b> have maximal possible distance from the <b><i>rrp₈</i></b>. Symbols as in Fig. 1.</p

Selection of maximally case-control survival discriminating combination of distances from all <i>RRP</i>'s.

<p>Points are defined by the coordinates (see text) computed by averaging the distance differences over all patients separately in case and control sub-cohorts for all 190 possible <b><i>RRP</i></b> pairs. In the neighborhood of diagonal line are non-discriminatory combinations. The two lines are used to identify the combinations, with maximal case – control and control-case bias in <b><i>PRP</i></b>-<b><i>RRP</i></b> distances. The optimal selection is shown by boxes.</p

Histograms showing heterogeneity of distributions of individuals shown in the CTLA-4 genotype landscape, defined by the inter-personal differences in <i>prp</i>'s for the five most discriminating <i>RRP</i> combinations.

<p>Two selected combination of distance differences are plotted on <b><i>x</i></b> and <b><i>y</i></b> axes, on the <b><i>z</i></b> axis are numbers of subjects having a given combination of the distance differences. Blue-controls, red-cases.</p

Study graphs <i>g</i>(a) and <i>G</i> (b) constructed as union of all <i>prp</i>'s (<i>g</i>) or <i>PRP</i>'s (<i>G</i>).

<p>Symbols as in Fig. 1, thickness of edges in <b><i>g</i></b> and <b><i>G</i></b> are proportional to co-occurrence frequencies of respective SNP pairs, connected by the edge.</p

Three examples showing how elements of distance vectors are computed for the same patient #55.

<p>In all figures, <b><i>prp</i></b><b>(</b><b><i>RRP</i></b> in <b>c)</b>) for this patient  =  dashed lines, <b><i>rrp</i></b>'s (or <b><i>RRP</i></b> in <b>c)</b>)  =  solid lines. Double arrows indicate mismatch in SNP co-occurrences. Elements of are sums of these mismatches (in computations, we add negative sign to make identity (zero mismatches) mathematically largest). <b>a,b)</b> Comparison of patient's genotype to the second and third reference SNP relationship patterns <b><i>rrp₃</i></b> and <b><i>rrp₂</i></b>_<b>.</b><b>c)</b> Comparison of patient's genotype to the 4^th reference SNP relationship pattern <b><i>RRP₄</i></b><b>.</b></p

Decomposition of study graphs <i>g</i> (picture represents both cases and control subcohorts) into <i>rrp</i>'s 1–8.

<p>Case <b><i>rrp</i></b>'s are shown by solid, control by dashed edges. Coefficients show the multiplicities of respective <b><i>rrp</i></b>'s in the <b><i>g</i></b>-decompositions (top  =  case graph, bottom  =  control graph). Symbols as in Fig. 1.</p