Overall the research integration in higher education is considered meaningful. It has also been argued that the inclusion of students in research through the curriculum differs between disciplines. Students of ‘hard’ disciplines are supposed to gain more seniority before the research discipline includes them, while students in ‘soft’ disciplines are invited sooner. While previous studies do confirm this trend line, also contradictoryresults have been found. Furthermore, the Biglan Framework (1973) provides more disciplinary differences than the often studied hard/soft divide. Moreover, the notion of involvement in research is more diverse than‘doing research’. Through an online survey this study systematically investigates undergraduate students’ experienced research integration for all study years of seven different faculties (N=2192). The findings indicateconfirmation of the claim that students of different disciplines are included in research at different moments in their educational track. However, this difference is not always based on the hard/soft divide.
MULTIFILE
Extended Reality (XR) technologies—including virtual reality (VR), augmented reality (AR), and mixed reality (MR)—offer transformative opportunities for education by enabling immersive and interactive learning experiences. In this study, we employed a mixed-methods approach that combined systematic desk research with an expert member check to evaluate existing pedagogical frameworks for XR integration. We analyzed several established models (e.g., TPACK, TIM, SAMR, CAMIL, and DigCompEdu) to assess their strengths and limitations in addressing the unique competencies required for XRsupported teaching. Our results indicate that, while these models offer valuable insights into technology integration, they often fall short in specifying XR-specific competencies. Consequently, we extended the DigCompEdu framework by identifying and refining concrete building blocks for teacher professionalization in XR. The conclusions drawn from this research underscore the necessity for targeted professional development that equips educators with the practical skills needed to effectively implement XR in diverse educational settings, thereby providing actionable strategies for fostering digital innovation in teaching and learning.
MULTIFILE
Gamma-band neuronal synchronization during sentence-level language comprehension has previously been linked with semantic unification. Here, we attempt to further narrow down the functional significance of gamma during language comprehension, by distinguishing between two aspects of semantic unification: successful integration of word meaning into the sentence context, and prediction of upcoming words. We computed eventrelated potentials (ERPs) and frequency band-specific electroencephalographic (EEG) power changes while participants read sentences that contained a critical word (CW) that was (1) both semantically congruent and predictable (high cloze, HC), (2) semantically congruent but unpredictable (low cloze, LC), or (3) semantically incongruent (and therefore also unpredictable; semantic violation, SV). The ERP analysis showed the expected parametric N400 modulation (HC < LC < SV). The time-frequency analysis showed qualitatively different results. In the gamma-frequency range, we observed a power increase in response to the CW in the HC condition, but not in the LC and the SV conditions. Additionally, in the theta frequency range we observed a power increase in the SV condition only. Our data provide evidence that gamma power increases are related to the predictability of an upcoming word based on the preceding sentence context, rather than to the integration of the incoming word's semantics into the preceding context. Further, our theta band data are compatible with the notion that theta band synchronization in sentence comprehension might be related to the detection of an error in the language input.
MULTIFILE
Prompt and timely response to incoming cyber-attacks and incidents is a core requirement for business continuity and safe operations for organizations operating at all levels (commercial, governmental, military). The effectiveness of these measures is significantly limited (and oftentimes defeated altogether) by the inefficiency of the attack identification and response process which is, effectively, a show-stopper for all attack prevention and reaction activities. The cognitive-intensive, human-driven alarm analysis procedures currently employed by Security Operation Centres are made ineffective (as opposed to only inefficient) by the sheer amount of alarm data produced, and the lack of mechanisms to automatically and soundly evaluate the arriving evidence to build operable risk-based metrics for incident response. This project will build foundational technologies to achieve Security Response Centres (SRC) based on three key components: (1) risk-based systems for alarm prioritization, (2) real-time, human-centric procedures for alarm operationalization, and (3) technology integration in response operations. In doing so, SeReNity will develop new techniques, methods, and systems at the intersection of the Design and Defence domains to deliver operable and accurate procedures for efficient incident response. To achieve this, this project will develop semantically and contextually rich alarm data to inform risk-based metrics on the mounting evidence of incoming cyber-attacks (as opposed to firing an alarm for each match of an IDS signature). SeReNity will achieve this by means of advanced techniques from machine learning and information mining and extraction, to identify attack patterns in the network traffic, and automatically identify threat types. Importantly, SeReNity will develop new mechanisms and interfaces to present the gathered evidence to SRC operators dynamically, and based on the specific threat (type) identified by the underlying technology. To achieve this, this project unifies Dutch excellence in intrusion detection, threat intelligence, and human-computer interaction with an industry-leading partner operating in the market of tailored solutions for Security Monitoring.
