Computer-based learning of spelling skills in children with and without dyslexia

Our spelling training software recodes words into multisensory representations comprising visual and auditory codes. These codes represent information about letters and syllables of a word. An enhanced version, developed for this study, contains an additional phonological code and an improved word selection controller relying on a phoneme-based student model. We investigated the spelling behavior of children by means of learning curves based on log-file data of the previous and the enhanced software version. First, we compared the learning progress of children with dyslexia working either with the previous software (n = 28) or the adapted version (n = 37). Second, we investigated the spelling behavior of children with dyslexia (n = 37) and matched children without dyslexia (n = 25). To gain deeper insight into which factors are relevant for acquiring spelling skills, we analyzed the influence of cognitive abilities, such as attention functions and verbal memory skills, on the learning behavior. All investigations of the learning process are based on learning curve analyses of the collected log-file data. The results evidenced that those children with dyslexia benefit significantly from the additional phonological cue and the corresponding phoneme-based student model. Actually, children with dyslexia improve their spelling skills to the same extent as children without dyslexia and were able to memorize phoneme to grapheme correspondence when given the correct support and adequate training. In addition, children with low attention functions benefit from the structured learning environment. Generally, our data showed that memory sources are supportive cognitive functions for acquiring spelling skills and for using the information cues of a multi-modal learning environment.     

Direct regional economic impact of Germany’s 1. FC Kaiserslautern through participation in the 1. Bundesliga

In discussions about the use of public money for popular sports such as clubs in Germany’s 1. Bundesliga, it is often argued that the funds are well invested due to the cash flows generated by these organizations for their home regions. However, others claim the opposite. They argue that actually no positive impact is generated and, even worse, that money is leaving the region due to the clubs. The study presented here analyses the financial flows generated by the 1. FC Kaiserslautern for its home city (Kaiserslautern) and home state (Rhineland-Palatinate) during the 2010/11 season when the club participated in the 1. Bundesliga. Based on a 3-step model, the economic impact is calculated by considering spectator spending and cash flows generated by the business activities of the club. It turns out that additional cash flows of approximately €16.5 million and €25.8 million were generated for the state and the city, respectively.     

Interdisciplinarity as diversity in citation patterns among journals: Rao-Stirling diversity,relative variety,and the Gini coefficient

Questions of definition and measurement continue to constrain a consensus on the measurement of interdisciplinarity. Using Rao-Stirling (RS) Diversity sometimes produces anomalous results. We argue that these unexpected outcomes can be related to the use of “dual-concept diversity” which combines “variety” and “balance” in the definitions (ex ante). We propose to modify RS Diversity into a new indicator (DIV) which operationalizes “variety,” “balance,” and “disparity” independently and then combines them ex post. “Balance” can be measured using the Gini coefficient. We apply DIV to the aggregated citation patterns of 11,487 journals covered by the Journal Citation Reports 2016 of the Science Citation Index and the Social Sciences Citation Index as an empirical domain and, in more detail, to the citation patterns of 85 journals assigned to the Web-of-Science category “information science & library science” in both the cited and citing directions. We compare the results of the indicators and show that DIV provides improved results in terms of distinguishing between interdisciplinary knowledge integration (citing references) versus knowledge diffusion (cited impact). The new diversity indicator and RS diversity measure different features. A routine for the measurement of the various operationalization of diversity (in any data matrix) is made available online.