Cognitive load theory, educational research, and instructional design: some food for thought

Cognitive load is a theoretical notion with an increasingly central role in the educational research literature. The basic idea of cognitive load theory is that cognitive capacity in working memory is limited, so that if a learning task requires too much capacity, learning will be hampered. The recommended remedy is to design instructional systems that optimize the use of working memory capacity and avoid cognitive overload. Cognitive load theory has advanced educational research considerably and has been used to explain a large set of experimental findings. This article sets out to explore the open questions and the boundaries of cognitive load theory by identifying a number of problematic conceptual, methodological and application-related issues. It concludes by presenting a research agenda for future studies of cognitive load

Software scaffolds to promote regulation during scientific inquiry learning

This research addresses issues in the design of online scaffolds for regulation within inquiry learning environments. The learning environment in this study included a physics simulation, data analysis tools, and a model editor for students to create runnable models. A regulative support tool called the Process Coordinator (PC) was designed to assist students in planning, monitoring, and evaluating their investigative efforts within this environment. In an empirical evaluation, 20 dyads received a “full” version of the PC with regulative assistance; dyads in the control group (n = 15) worked with an “empty” PC which contained minimal structures for regulative support. Results showed that both the frequency and duration of regulative tool use differed in favor of the PC+ dyads, who also wrote better lab reports. PC− dyads viewed the content helpfiles more often and produced better domain models. Implications of these differential effects are discussed and suggestions for future research are advanced

What Can Be Learned from Computer Modeling? Comparing Expository and Modeling Approaches to Teaching Dynamic Systems Behavior

Computer modeling has been widely promoted as a means to attain higher order learning outcomes. Substantiating these benefits, however, has been problematic due to a lack of proper assessment tools. In this study, we compared computer modeling with expository instruction, using a tailored assessment designed to reveal the benefits of either mode of instruction. The assessment addresses proficiency in declarative knowledge, application, construction, and evaluation. The subscales differentiate between simple and complex structure. The learning task concerns the dynamics of global warming. We found that, for complex tasks, the modeling group outperformed the expository group on declarative knowledge and on evaluating complex models and data. No differences were found with regard to the application of knowledge or the creation of models. These results confirmed that modeling and direct instruction lead to qualitatively different learning outcomes, and that these two modes of instruction cannot be compared on a single “effectiveness measure”

Validating and optimizing the effects of model progression in simulation-based inquiry learning

Model progression denotes the organization of the inquiry learning process in successive phases of increasing complexity. This study investigated the effectiveness of model progression in general, and explored the added value of either broadening or narrowing students’ possibilities to change model progression phases. Results showed that high-school students in the ‘standard’ model progression condition (n = 19), who could enter subsequent phases at will, outperformed students from a control condition (n = 30) without model progression. The unrestricted condition (n = 22) had the additional option of returning to previous phases, whereas the restricted condition (n = 20) disallowed such downward progressions as well as upward progressions in case insufficient knowledge was acquired. Both variants were found to be more effective in terms of performance than the ‘standard’ form of model progression. However, as performance in all three model progression conditions was still rather weak, additional support is needed for students to reach full understanding of the learning content

Conformality Lost

We consider zero-temperature transitions from conformal to non-conformal phases in quantum theories. We argue that there are three generic mechanisms for the loss of conformality in any number of dimensions: (i) fixed point goes to zero coupling, (ii) fixed point runs off to infinite coupling, or (iii) an IR fixed point annihilates with a UV fixed point and they both disappear into the complex plane. We give both relativistic and non-relativistic examples of the last case in various dimensions and show that the critical behavior of the mass gap behaves similarly to the correlation length in the finite temperature Berezinskii-Kosterlitz-Thouless (BKT) phase transition in two dimensions, xi ~ exp(c/|T-T_c|^{1/2}). We speculate that the chiral phase transition in QCD at large number of fermion flavors belongs to this universality class, and attempt to identify the UV fixed point that annihilates with the Banks-Zaks fixed point at the lower end of the conformal window.Comment: 30 pages, 6 figures; v2: typos fixed, references adde

Determinants of Growth of Start-ups in the Netherlands

The dynamics and growth of firms are considered to be important for enhancing economic growth. Organizations can benefit from growth in many ways, including greater efficiency through economies of scale, increased power, the ability to withstand environmental change, increased profit and increased prestige for organizational members.It is important to obtain a better grip on the growth development of start-ups. The aim of this study is to map the development of start-ups in terms of employment growth and, in addition, to understand: what are the determinants of growth of start-ups?