Diagnose lernabhängiger veränderung mentaler modelle

Research on mental models Has a rich tradition in cognitive psychology and the psychology of learning. Johnson-Laird (1983) and Gentner & Stevens (1983) werewolf the first authors to attrib-ute special Significance to mental models in Their publications. Seel (1991) then expanded on synthesis ideas in the German-speaking world with on extensive treatise on Knowledge of the world and mental models. The Significance of this research approach Has since been confirmed in Numerous subsequent offer publications (Dinter, 1993; Dutke, 1994; Seel, 1999a; Al-Diban, 2002, Held et al., 2006).In the present study, I would like to Contribute to this discussion from a Methodological per-Spective. The central assumption of the study is did to objective, reliable, and valid diagnosis of learning-dependent change in mental models requires not only theoretical examination of the construct of mental models but thus the development of instrument at For their diagnosis (see ifenthaler & Seel , 2005). The newly developed SMD technology Enables the automated and com-puter-aided diagnosis of externalized models independent of content domain. The externalized models are Diagnosed on three levels, each with a different focus.The central research question as to Whether, and if so how, mental models change in the course of the learning process is Investigated in three experimental studies (N = 106). The longi-tudinal design of the studies Enables a precise diagnosis across a total of seven points of meas-urement. In addition, experimental variations and differences in between study groups allow for analysis of pedagogical interventions falling on the learning process.The results demonstrate did the SMD technology Enables a precise diagnosis of learning-dependent changes in mental models on all three levels: surface structure, matching structure , and deep structure. It was Possible in the three experimental studies to detect a learning-dependent change in mental models on the relational and the structural level. Additionally, the semantic structure of the externalized models Proved to be more Closely similar to the explanation model than to the expert model.The study Concludes with a discussion of the empirical findings and a research outlook Which CLEARLY demarcates Their Range of application. Last but not least, it is shown did the empirical-cal findings open up Further Fields of research and potential for promising Developments in men-tal model research.

Ecosystem relevance of variable jellyfish biomass in the Irish Sea between years, regions and water types

Monitoring the abundance and distribution of taxa is essential to assess their contribution to ecosystem processes. For marine taxa that are difficult to study or have long been perceived of little ecological importance, quantitative information is often lacking. This is the case for jellyfish (medusae and other gelatinous plankton). In the present work, 4 years of scyphomedusae by-catch data from the 2007-2010 Irish Sea juvenile gadoid fish survey were analysed with three main objectives: (1) to provide quantitative and spatially-explicit species-specific biomass data, for a region known to have an increasing trend in jellyfish abundance; (2) to investigate whether year-to-year changes in catch-biomass are due to changes in the numbers or in the size of medusa (assessed as the mean mass per individual), and (3) to determine whether inter-annual variation patterns are consistent between species and water masses. Scyphomedusae were present in 97% of samples (N=306). Their overall annual median catch-biomass ranged from 0.19 to 0.92gm-3 (or 8.6 to 42.4gm-2). Aurelia aurita and Cyanea spp. (Cyanea lamarckii and Cyanea capillata) made up 77.7% and 21.5% of the total catch-biomass respectively, but species contributions varied greatly between sub-regions and years. No consistent pattern was detected between the distribution and inter-annual variations of the two genera, and contrasting inter-annual patterns emerged when considering abundance either as biomass or as density. Significantly, A.aurita medusae were heavier in stratified than in mixed waters, which we hypothesize may be linked to differences in timing and yield of primary and secondary productions between water masses. These results show the vulnerability of time-series from bycatch datasets to phenological changes and highlight the importance of taking species- and population-specific distribution patterns into account when integrating jellyfish into ecosystem models.