Publications

There is increasing scholarly agreement about the key features of academically productive classroom dialogue, as well as about its role in student learning and growth. Yet, despite this emerging conceptual consensus, the ways in which it is measured and coded in quantitative research efforts vary significantly across settings, research teams, and studies. In order to communicate, compare and integrate findings from this rich body of empirical research and to further theory refinement, a more uniform approach to measuring classroom dialogue is needed. In this paper, we argue that for such an approach to succeed it should meet the following requirements: It should enable stable coding across settings and raters (reliability), be capable of capturing a wide variety of dialogue features (comprehensiveness) and enable different types of research questions and analyses (flexibility). Given the current conceptual maturity, as well as the vast number of quantitative studies that have accumulated in the last two decades, we believe that the field has sufficiently matured to achieve this goal. We selected seven well-known and validated coding frameworks for academically productive classroom dialogue. Through an iterative process of comparison, deconstruction, and application to classroom dialogue transcripts, we identified a set of nine elementary particles, so-called dialogue elements (DEs), that are common across the different coding categories and can be reliably coded at the conversational turn level. We then demonstrate how a much larger set of "compound" dialogue constructs can be identified post-coding by flagging co-occurrences of different DEs that recreate higher-order dialogue constructs. With the help of this Dialogue Elements to Compound Constructs Approach (DECCA), the majority of coding categories from each of the seven selected coding frameworks could be recreated. DECCA thus enables interrater reliability, while simultaneously maintaining the flexibility and comprehensiveness needed to enable research on a large variety of questions with a single methodological approach. The implications, limitations and for future research and theory are discussed.

Multiscale simulations have been established as a powerful tool to calculate and predict excitation energies in complex systems such as photoreceptor proteins. In these simulations the chromophore is typically treated using quantum mechanical (QM) methods while the protein and surrounding environment are described by a classical molecular mechanics (MM) force field. The electrostatic interactions between these regions are often treated using electrostatic embedding where the point charges in the MM region polarize the QM region. A more sophisticated treatment accounts also for the polarization of the MM region. In this work, the effect of such a polarizable embedding on excitation energies was benchmarked and compared to electrostatic embedding. This was done for two different proteins, the lipid membrane-embedded jumping spider rhodopsin and the soluble cyanobacteriochrome Slr1393g3. It was found that the polarizable embedding scheme produces absorption maxima closer to experimental values. The polarizable embedding scheme was also benchmarked against expanded QM regions and found to be in qualitative agreement. Treating individual residues as polarizable recovered between 50% and 71% of the QM improvement in the excitation energies, depending on the system. A detailed analysis of each amino acid residue in the chromophore binding pocket revealed that aromatic residues result in the largest change in excitation energy compared to the electrostatic embedding. Furthermore, the computational efficiency of polarizable embedding allowed it to go beyond the binding pocket and describe a larger portion of the environment, further improving the results.

Individual entities across levels of biological organization interact to reach collective decisions. In centralized neuronal networks, competing neural populations commonly accumulate information over time while increasing their own activity, and cross-inhibiting other populations until one group passes a given threshold. In social insects, there is good evidence for decisions mediated by positive feedbacks, but we found evidence for similar inhibitory signals only in honey bee (Apis mellifera) stop signals, and Pharaoh’s ant (Monomorium pharaonic) repellent pheromones, with only the former occasionally being used as cross-inhibition. We discuss whether these differences stem from insufficient research effort or represent genuine differences across levels of biological organization.

The current challenges of structural biophysics include determining the structure of large self-assembled complexes, resolving the structure of ensembles of complex structures and their mass fraction, and unraveling the dynamic pathways and mechanisms leading to the formation of complex structures from their subunits. Modern synchrotron solution X-ray scattering data enable simultaneous high-spatial and high-temporal structural data required to address the current challenges of structural biophysics. These data are complementary to crystallography, NMR, and cryo-TEM data. However, the analysis of solution scattering data is challenging; hence many different analysis tools, listed in the SAS Portal (http://smallangle.org/), were developed. In this review, we start by briefly summarizing classical X-ray scattering analyses providing insight into fundamental structural and interaction parameters. We then describe recent developments, integrating simulations, theory, and advanced X-ray scattering modeling, providing unique insights into the structure, energetics, and dynamics of self-assembled complexes. The structural information is essential for understanding the underlying physical chemistry principles leading to self-assembled supramolecular architectures and computational structural refinement.

Bumble bees are eusocial bees in which the division of labor in reproduction and in task performance changes during their annual life cycle. The queen monopolizes reproduction in young colonies, but at later stages some workers start to challenge the queen and lay their own unfertilized eggs. The division of colony maintenance and growth tasks relates to worker body size. Reproduction and task performance are regulated by multiple social signals of the queen, the workers, and the brood. Here we review recent studies suggesting that bumble bees use multiple sources of information to establish and maintain division of labor in both reproduction and in task performance. Juvenile hormone is an important neuroendocrine signal involved in the regulation of division of labor in reproduction but not in worker task performance. The reliance on multiple signals facilitate flexibility in face of changes in the social and geophysical environment. Data Availability No data were used for the research described in the article.

Group leaders play a vital role in divided cities, particularly in local problem-solving and in everyday contestations. Their role as negotiators makes them perfectly positioned to promote urban processes for the group to which they belong but also raises questions regarding their loyalty. Seeking to understand these individuals’ thinking, this study asks how leaders from different groups in a divided city explain their development as leaders. Utilizing a life-story approach, we present a narrative analysis of 40 life-stories, as told by local leaders representing the main social groups in Jerusalem. Our findings suggest that leaders from different groups use distinctive narratives to ensure their relevancy: “The Homecomer,” used by Israeli-Jews; “The Middleman,” used by Palestinian-Arabs; and “The Pathfinder,” used by Israeli Ultraorthodox-Jews. More importantly, we found that all these leaders share a similar mind-set, what we call leadership development as discovery. Indeed, their development includes formative events that differentiate them from their community, helping them to see the divided city from a different perspective and positioning them as leaders. Understanding and acknowledging this spatial aspect in their narratives can be a first step in facilitating group collaborations, empowering local leaders, and even leading to the emergence of new ones. Our implications go beyond divided cities and can be further studied in ordinary cities.

Over the past decade, rapid technological advancements and budget constraints have increased the demand for online education (Martin et al., 2020). Furthermore, the COVID-19 pandemic has vastly accelerated this trend, compelling almost all education providers to migrate their courses to online learning platforms (Theelen & Van Breukelen, 2022). In view of other profound crises that affect mobility, such as climate change, political instabilities and future pandemics, it is safe to assume that online learning will remain in demand, even in a post-pandemic world ) (Bayne et al., 2020). In this context, while educational research  has  made  significant  progress  in  establishing  design  principles  that  ensure  effective  online teaching  and  learning,  the  main  focus  of  this  scholarly  work  is  on  the  acquisition  of  declarative knowledge  and  cognitive  skills.  Moreover,  since  very  little  is  known  about  the  online  teaching  and distance  learning  of  psychomotor skills  (Kouhia  et  al.,  2021;  Lehtiniemi  et  al.,  2023),  this  paper  and 
exhibition  explore  how  eye-tracking  technology  (ETT)  creates  unique  opportunities  to  improve  craft education in hybrid and distant learning settings.

How is the electoral behavior of minorities shaped by past violence? Recent studies found that displacement increases hostility between perpetrators and displaced individuals, but there has been paltry research on members of surviving communities. We argue that the latter exhibit the opposite pattern because of their different condition. Violence will cause cross-generational vulnerability, fear and risk-aversion— leading the surviving communities to seek protection and avoid conflict by signalling loyalty and rejecting nationalist movements. In their situation as an excluded minority in the perpetrators’ state, they will be more likely to vote for out-group parties. Exploiting exogenous battlefield dynamics that created inter-regional variation in the Palestinian exodus (1947-1949), microlevel measurements that capture the damage of violence, and an original longitudinal data set, we show that Palestinian villages in Israel more severely impacted by the 1948 war have a much higher vote share to Jewish parties even seventy years later. Survey evidence further supports our theory, revealing that this pattern exists only for members of the surviving communities, and not among displaced individuals. The findings shed new light on the complex social relations that guide political decision-making in post-war settings and divided societies that suffer from protracted conflicts.

In quantitative content analysis, conventional wisdom holds that reliability, operationalized as agreement, is a necessary precondition for validity. Underlying this view is the assumption that there is a definite, unique way to correctly classify any instance of a measured variable. In this intervention, we argue that there are textual ambiguities that cause disagreement in classification that is not measurement error, but reflects true properties of the classified text. We introduce a notion of valid disagreement, a form of replicable disagreement that must be distinguished from replication failures that threaten reliability. We distinguish three key forms of meaning multiplicity that result in valid disagreement – ambiguity due to under-specification, polysemy due to excessive information, and interchangeability of classification choices – that are widespread in textual analysis, yet defy treatment within the confines of the existing content-analytic toolbox. Discussing implications, we present strategies for addressing valid disagreement in content analysis.