This article presents the design and a first pilot evaluation of the computer-based training program Calcularis for children with developmental dyscalculia (DD) or difficulties in learning mathematics. The program has been designed according to insights on the typical and atypical development of mathematical abilities. The learning process is supported through multimodal cues, which encode different properties of numbers. To offer optimal learning conditions, a user model completes the program and allows flexible adaptation to a child's individual learning and knowledge profile. Thirty-two children with difficulties in learning mathematics completed the 6–12-weeks computer training. The children played the game for 20 min per day for 5 days a week. The training effects were evaluated using neuropsychological tests. Generally, children benefited significantly from the training regarding number representation and arithmetic operations. Furthermore, children liked to play with the program and reported that the training improved their mathematical abilities.

Many children show negative emotions related to mathematics and some even develop mathematics anxiety. The present study focused on the relation between negative emotions and arithmetical performance in children with and without developmental dyscalculia (DD) using an affective priming task. Previous findings suggested that arithmetic performance is influenced if an affective prime precedes the presentation of an arithmetic problem. In children with DD specifically, responses to arithmetic operations are supposed to be facilitated by both negative and mathematics-related primes (=negative math priming effect).We investigated mathematical performance, math anxiety, and the domain-general abilities of 172 primary school children (76 with DD and 96 controls). All participants also underwent an affective priming task which consisted of the decision whether a simple arithmetic operation (addition or subtraction) that was preceded by a prime (positive/negative/neutral or mathematics-related) was true or false. Our findings did not reveal a negative math priming effect in children with DD. Furthermore, when considering accuracy levels, gender, or math anxiety, the negative math priming effect could not be replicated. However, children with DD showed more math anxiety when explicitly assessed by a specific math anxiety interview and showed lower mathematical performance compared to controls. Moreover, math anxiety was equally present in boys and girls, even in the earliest stages of schooling, and interfered negatively with performance. In conclusion, mathematics is often associated with negative emotions that can be manifested in specific math anxiety, particularly in children with DD. Importantly, present findings suggest that in the assessed age group, it is more reliable to judge math anxiety and investigate its effects on mathematical performance explicitly by adequate questionnaires than by an affective math priming task.

Aktuelle Studienergebnisse verdeutlichen, dass sich Kinder bereits im frühen Grundschulalter hinsichtlich ihrer Mathematikangst unterscheiden und dass diese mit deren Mathematikleistung korreliert (Vukovic et al., 2013;Wu et al., 2012

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Intelligent tutoring systems are adapting the curriculum to the needs of the student. The integration of stealth assessments of student traits into tutoring systems, i.e. the automatic detection of student characteristics has the potential to re?ne this adaptation. We present a pipeline for integrating automatic assessment seamlessly into a tutoring system and apply the method to the case of developmental dyscalculia (DD). The proposed classi?er is based on user inputs only, allowing non-intrusive and unsupervised, universal screening of children. We demonstrate that interaction logs provide enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91% after 11 minutes on average. Abstract. Intelligent tutoring systems are adapting the curriculum to the needs of the student. The integration of stealth assessments of student traits into tutoring systems, i.e. the automatic detection of student characteristics has the potential to refine this adaptation. We present a pipeline for integrating automatic assessment seamlessly into a tutoring system and apply the method to the case of developmental dyscalculia (DD). The proposed classifier is based on user inputs only, allowing non-intrusive and unsupervised, universal screening of children. We demonstrate that interaction logs provide enough information to identify children at risk of DD with high accuracy and validity and reliability comparable to traditional assessments. Our model is able to adapt the duration of the screening test to the individual child and can classify a child at risk of DD with an accuracy of 91% after 11 minutes on average.Keywords: automatic assessment, feature processing, Bayesian network, pairwise clustering, computer-based screening, dyscalculia Intelligent tutoring systems (ITS) are gaining importance in education. A lot of research has been conducted to represent and model student knowledge accurately, design effective curricula and develop optimal instructional policies. A large body of work has focused on mining the data logs collected from ITS. Important topics in this area are automatic stealth assessments such as the evaluation of student learning or detection of student properties (e.g. intelligence, learning disabilities) [31]. Traditional assessments are often time consuming and have to be supervised by an expert, rendering them expensive in practice. Hence, this approach does not scale and is therefore not suitable in many cases, such as MOOCs, large university courses, or widespread screenings in elementary schools to enable early detection of learning disabilities.Previous work has investigated stand-alone automatic digital assessments, including research on automatic scoring [5], item generation [18] and game-based assessment [20]. Furthermore, digital screening programs replacing traditiona...

Zusammenfassung. Ziel der vorliegenden Studie ist die Überprüfung des Einflusses eines computerisierten Rechentrainings (Calcularis) auf psychische Auffälligkeiten, Selbstbewertungen der eigenen Leistungsfähigkeit und Leistungsängste. 68 rechenschwache Kinder wurden zufällig einer von drei Studienbedingungen (Calcularis-(CG), Wartekontroll-(WKG), nicht-mathematikbezogene Kontrolltrainingsgruppe (KTG)) zugeordnet. Generell bestätigte sich eine größere emotionale Belastung der rechenschwachen Kinder. Die Ergebnisse zur unmittelbaren Wirksamkeit zeigten eine deutlich stärkere Reduktion der Mathematikangst bei Kindern der CG im Vergleich zur WKG, während sich keine Unterschiede zwischen den Trainingsgruppen ergaben. Zudem verbesserten sich die Gruppen gleichermaßen in Bezug auf die Selbsteinschätzung und Einstellung zum Fach Mathematik und das kognitive Selbstkonzept. Längerfristig, fünf Monate nach Trainingsabschluss, zeigte sich eine vergleichbare Verbesserung beider Trainingsgruppen hinsichtlich der sozio-emotionalen Merkmale, während die psychischen Auffälligkeiten auf einem stabilen Niveau blieben. In Bezug auf die Selbsteinschätzung und Einstellung zum Fach Mathematik wies die KTG eine stärkere Verbesserung auf als die CG. Die Befunde werden unter Berücksichtigung besonderer Stichprobencharakteristika, wie dem hohen Anteil komorbider Schwächen der Schriftsprache in der KTG, diskutiert. Erstmals wurde vorliegend die Reduktion der Mathematikangst in Folge eines Rechentrainings nachgewiesen.

Research has shown that learning disabilities are associated with internalizing problems in (pre)adolescents. In order to examine this relationship for math disability (MD), math achievement and internalizing problem scores were measured in a representative group of 1,436 (pre)adolescents. MD was defined by a discrepancy between math achievement and IQ. Internalizing problems were measured through a multi-informant (parents, teachers, self-report) approach. The results revealed that MD puts (pre)adolescents at a higher risk for internalizing problems. External and self-ratings differed between boys and girls, indicating that either they show distinct internalizing symptoms or they are being perceived differently by parents and teachers. Results emphasize the importance of both a multi-informant approach and the consideration of gender differences when measuring internalizing symptomatology of children with MD. For an optimal treatment of MD, depressive and anxious symptoms need to be considered.