The network approach to assess the structure of knowledge : Storage, distribution and retrieval as three measures in analysing concept maps

We present three new standardised network concept map (CM) measures that can provide unique information about learning-related progress, which cannot be determined from previously known measures. Grounded in cognitive development theory on the one hand, and network theory on the other hand, our measures reveal how knowledge is stored, distributed and retrieved. We validated the new measures by testing their ability to discriminate between CMs of respondents with different levels of competency in statistics (students before and after taking an introductory statistics course and experts in the field of statistics). We also validated our measures against the most commonly used traditional and network measures. Based on a small sample of respondents, we show that two of the newly proposed compound measures reveal significant differences between experts and novices in the field, with higher values for experts, showing that expert knowledge is better distributed, more connected and balanced. More importantly, our measures were sensitive enough to show learning-related progress for students, albeit statistically non-significant, while common indicators from network theory did not demonstrate these small shifts. The validity of our new measures can be inferred from the consistency of the results from different sets of measures.Peer reviewe

Resilience and Effective Learning in First-Year Undergraduate Computer Science

Many factors have been shown to be important for supporting effective learning and teaching — and thus progression and success — in higher education. While factors such as key introductory-level (CS1) knowledge and skills, as well as pre-university learning and qualifications, have been extensively explored, the impact of measures of positive psychology are less well understood for the discipline of computer science. University study can be a period of significant transition for many students; therefore an individual’s positive psychology may have considerable impact upon their response to these challenges. This work investigates the relationships between effective learning and success (first-year performance and attendance) and two measures of positive psychology: Grit and the Nicolson McBride Resilience Quotient (NMRQ).Data was captured by integrating Grit (N=58) and Resilience (N=50) questionnaires and related coaching into the first-year of the undergraduate computer science programme at a single UK university. Analyses demonstrate that NMRQ is significantly linked to attendance and performance for individual subjects and year average marks; however, this was not the case for Grit. This suggests that development of targeted interventions to support students in further developing their resilience could support their learning, as well as progression and retention. Resilience could be used, in concert with other factors such as learning analytics, to augment a range of existing models to predict future student success, allowing targeted academic and pastoral support

Валидность теста: между научностью и полезностью. История изменений ключевого понятия психологического тестирования

В истории количественной психологии и психометрики валидность теста всегда рассматривалась как мера его качества, так что техническая сторона валидизации и требования к валидному тесту всегда были хорошо освещены в литературе. Однако понятие «валидность» претерпело столь фундаментальные изменения, что они не могут быть осмыслены только с технической точки зрения в отрыве от изменений социального контекста, в котором существует психометрика. В этой статье произошедшие изменения подхода к валидности рассматриваются в свете дилеммы научности vs. практической полезности тестов. Демонстрируется, что требования к валидному тесту постепенно вытесняли научный вопрос (что измеряет тест) в пользу практического вопроса о полезности теста и его корректном использовании. Эти изменения прочно связаны с возрастанием роли тестирования в принятии социально значимых решений

Effective learning and resilience in first year undergraduate computer science

Many factors have been shown to be important for maintaining effective learning and achieving success in higher education; more specifically in Computer Science. While factors such as existing student competencies and abilities have been extensively explored, the impact of measures of positive psychology are less well understood in this context. University study can be a period of significant transition for all students, therefore an individual's positive psychology may have considerable impact upon their response to these challenges. This work investigates the relationships between effective learning and success (first year performance and attendance) and two measures of positive psychology: Grit and the Nicolson McBride Resilience Quotient (NMRQ). Data was captured by integrating Grit and Resilience questionnaires and related coaching into the first year of computer science at a UK University. Analyses demonstrate that NMRQ is significantly linked to attendance and performance for individual subjects and year average marks, however, this is not so for grit. This suggests that further development of interventions to help support students in further developing their resilience could be productive. Resilience could be used, in concert with other factors, to augment a range of existing models to predict future student success, permitting targeted support