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Abstract We here defined the impacts of γ-secretase inhibitors (GSIs) on T-cell-dependent BCMA-specific multiple myeloma (MM) cell lysis and immunomodulatory effects induced by bispecific antibodies (BisAbs). GSIs-induced membrane BCMA (mBCMA) accumulation reached near maximum within 4 h and sustained over 42h-study period on MM cell lines and patient MM cells. GSIs, i.e., 2 nM LY-411575 or 1 μM DAPT, robustly increased mBCMA densities on CD138+ but not CD3+ patient cells, concomitantly with minimum soluble/shed BCMA (sBCMA) in 1 day-culture supernatants. In ex vivo MM-T-cell co-cultures, GSIs overcame sBCMA-inhibited MM cell lysis and further enhanced autologous patient MM cell lysis induced by BCMAxCD3 BisAbs, accompanied by significantly enhanced cytolytic markers (CD107a, IFNγ, IL2, and TNFα) in patient T cells. In longer 7 day-co-cultures, LY-411575 minimally affected BCMAxCD3 BisAb (PL33)-induced transient expression of checkpoint (PD1, TIGIT, TIM3, LAG3) and co-stimulatory (41BB, CD28) proteins, as well as time-dependent increases in % effector memory/central memory subsets and CD8/CD4 ratios in patient T cells. Importantly, LY41157 rapidly cleared sBCMA from circulation of MM-bearing NSG mice reconstituted with human T cells and significantly enhanced anti-MM efficacy of PL33 with prolonged host survival. Taken together, these results further support ongoing combination BCMA-targeting immunotherapies with GSI clinical studies to improve patient outcome.

CD3-engaging bispecific antibodies (BsAbs) enable the formation of an immune synapse between T cells and tumor cells, resulting in robust target cell killing not dependent on a preexisting tumor specific T cell receptor. While recent studies have shed light on tumor cell-specific factors that modulate BsAb sensitivity, the T cell-intrinsic determinants of BsAb efficacy and response durability are poorly understood. To better clarify the genes that shape BsAb-induced T cell responses, we conducted targeted analyses and a large-scale unbiased in vitro CRISPR/Cas9-based screen to identify negative regulators of BsAb-induced T cell proliferation. These analyses revealed that CD8+ T cells are dependent on CD4+ T cell-derived signaling factors in order to achieve sustained killing in vitro. Moreover, the mammalian target of rapamycin (mTOR) pathway and several other candidate genes were identified as intrinsic regulators of BsAb-induced T cell proliferation and/or activation, highlighting promising approaches to enhancing the utility of these potent therapeutics.

Central goals of higher education in STEM domains include learning of problem solving and self-assessment skills. To achieve these goals, we propose a novel self-assessment method called the Solve-Correct-Assess-Negotiate (SCAN) method of assessing problem solving that includes both formative and summative elements. We study students’ learning experiences in courses involving different methods of assessing problem solving (Course 1 including teacher-led assessment, Ntrad = 53; Course 2 including SCAN method, NSCAN = 56) and specifically associations between these learning experiences and students' perceptions of the SCAN method. We found that the students relied on teacher-led assessment more than the self-assessment. The perceived utility of the self-assessment was positively associated with a deeper approach to learning in Course 2 than in Course 1. Students who found the self-assessment less beneficial also perceived less support from the learning environment. Our findings suggest that the successful implementation of novel self-assessment-based practices for problem-solving requires personalized support for self-assessment, teachers’ awareness of the different perceptions that students have towards these practices, and discussion among teachers and students on the rationale, utility, and reliability of the different practices.

In this paper we conceptualize formative peer feedback principles by analyzing and comparing six empirical examples of formative peer feedback in a set of international STEM (science, technology, engineering, and mathematics) contexts. By discussing how these different approaches to peer feedback unfold in practice, we aim to facilitate the bridging of the gap between theory and practice in implementing peer feedback in Higher Education. As a group of researchers and teaching practitioners from six Higher Education institutions, we discussed, analyzed, and synthesized practical examples of peer feedback in STEM that cover a breadth of settings, aims, and forms. The analysis and comparison of these examples illustrate how principles in peer feedback emerge in practice. We discuss how the context in peer feedback influences its practical implementation, particularly with regard to its purpose and aims, the development and use of assessment criteria, and embedding and supporting the initiatives into the teaching and learning activities.

Citizen science (CS) is a growing field of participatory science, bringing together the public, researchers, organizations, and communities to participate in various scientific projects that unfold in different sociomaterial settings known as territories. While research on perceived learning in CS has recently grown, the discussion regarding the different learning approaches, territories, and the overall process as well as their associations with learning factors remains meager. In our study, we unpack three types of learning (formal, informal, and nonformal) and their respective territories in CS, and within this context, review a model of learning to synthesize the project-related and individual factors associated with the perceived learning of citizen scientists engaged in CS activities. We conducted an international survey for adults participating in CS, which was then analyzed using exploratory factor analysis (N = 596). We identified the following five factors regarding CS activities and perceived learning: sociomaterial learning, social learning, reflective learning, situational learning, and material learning. We found that perceived learning was lower for citizen scientists who participated in biology CS projects but higher among citizen scientists who participated in the long term and engaged in a variety of CS activities. Our findings highlight that the learning experiences of citizen scientists can be varied within a CS project because of the varied entanglements of project-related and individual factors, which can be better understood through a model of learning. Our findings contribute to developing further the theories and practices related to CS and CS in education.

Although eye tracking has been successfully used in science education research, exploiting its potential in collaborative knowledge construction has remained sporadic. This article presents a novel approach for studying collaborative knowledge construction in a simulation-based environment by combining both the spatial and temporal dimensions of eye-tracking data with video data. For this purpose, we have investigated two undergraduate physics student pairs solving an electrostatics problem in a simulation-based environment via Zoom. The analysis of the video data of the students’ conversations focused on the different collaborative knowledge construction levels (new idea, explication, evaluation, and non-content-related talk and silent moments), along with the temporal visualizations of the collaborative knowledge construction processes. The eye-tracking data of the students’ gaze, as analyzed by epistemic network analysis, focused on the pairs’ spatial and temporal gaze behavior. We illustrate how gaze behavior can shed light on collaborative knowledge construction in terms of the quantity of the talk (e.g., gaze behavior can shed light on the different activities of the pairs during the silent moments), quality of the talk (e.g., gaze behavior can shed light on the different approaches when constructing knowledge on physical phenomena), and temporality of collaborative knowledge construction processes [e.g., gaze behavior can shed light on (the lack of) attempts to acquire the supporting or contrasting evidence on the initial ideas on the physical phenomena]. We also discuss the possibilities and limitations of gaze behavior to reveal the critical moments in the collaborative knowledge construction processes.

Staying at the front line in learning research is challenging because many fields are rapidly developing. One such field is research on the temporal aspects of computer-supported collaborative learning (CSCL). To obtain an overview of these fields, systematic literature reviews can capture patterns of existing research. However, conducting systematic literature reviews is time-consuming and do not reveal future developments in the field. This study proposes a machine learning method based on topic modelling that takes articles from a systematic literature review on the temporal aspects of CSCL (49 original articles published before 2019) as a starting point to describe the most recent development in this field (52 new articles published between 2019 and 2020). We aimed to explore how to identify new relevant articles in this field and relate the original articles to the new articles. First, we trained the topic model with the Results, Discussion, and Conclusion sections of the original articles, enabling us to correctly identify 74% (n = 17) of new and relevant articles. Second, clusterisation of the original and new articles indicated that the field has advanced in its new and relevant articles because the topics concerning the regulation of learning and collaborative knowledge construction related 26 original articles to 10 new articles. New irrelevant studies typically emerged in clusters that did not include any specific topic with a high topic occurrence. Our method may provide researchers with resources to follow the patterns in their fields instead of conducting repetitive systematic literature reviews.

Context: This research was conducted in the context of Finnish vocational education and training (VET) teacher training. The teacher training was work-based, meaning that each teacher trainee was already working as an unqualified VET teacher. Workplaces were comprehensively utilised as the learning environment, with teacher training support also being provided in the form of contact days, webinars, and online learning activities. Approach: We aimed to explore the main components of information and communications technology (ICT) competencies among vocational teacher trainees within work-based training and also to reveal the supportive and challenging factors related to developing ICT competencies within the training. Overall, 44 vocational teacher trainees participated in our study. The data were analysed via qualitative content analysis. Findings: Six main ICT competence components were identified during the work-based training: (1) The use and creation of digital learning materials, (2) the planning and use of digital learning environments, (3) synchronous digitally enhanced teaching, (4) general ICT competencies, (5) digital interaction, and (6) digital assessment. The development of teachers' ICT competencies was supported by their own active use of ICT and by experimenting with the ICT software and ideas presented by the teacher training staff. Challenging factors in ICT development included the continuous feeling of haste and the lack of time in the workplace, as well as the failure to recognise prior ICT competencies within the teacher training. This could limit the development of ICT competencies. Conclusions: Work-based VET teacher training has the potential to develop teacher trainees' ICT competencies because it allows immediate implementation and experimentation with regard to new ICT ideas and tools. By aligning this research with prior research, it is possible to construct a comprehensive ICT competence framework to support VET teacher training and workplace development.

Abstract Background Productive learning processes and good learning outcomes can be attained by applying the basic elements of active learning. The basic elements include fostering discussions and disputations, facing alternative conceptions, and focusing on conceptual understanding. However, in the face of poor course retention and high dropout rates, even learning outcomes can become of secondary importance. To address these challenges, we developed a research-based instructional strategy, the primetime learning model. We devised the model by organizing the basic elements of active learning into a theory-based four-step study process. The model is based on collaborative and technology-enhanced learning, on versatile formative assessment without a final exam, and on genuine teacher presence through intimate meetings between students and teachers. Results We piloted the model in two university physics courses on thermodynamics and optics and observed persistent student activity, improved retention, and good learning outcomes. Feedback suggested that most students were satisfied with the learning experience. Conclusions The model suits particularly well for courses that, in addition to the teaching subject itself, focus on teaching balanced study habits and strengthening social integration. By its very construction, it also helps the propagation of research-based instructional strategies. Although the model does contain challenges, it represents a generic framework for learning and teaching that is flexible for further development and applicable to many subjects and levels.

In this study, we introduce new insights into prosodic analyses as an emerging method to study teacher talk. We claim that the prosodic aspects (features of speech such as intonation, volume, and pace) of talk are important, but under-represented in the learning sciences. These prosodic aspects may be used to complement, intensify or even reverse the linguistic content of speech. Thus far, most research on classrooms has focused on the content (what is said) rather than on understanding the meaning of the prosodic features (how it is said) of talk. In this study, we introduce prosodic analyses as a method to study classroom discussions. Our exploratory experiment focuses on the prosodic perspective of teacher’s talk to shed light on the features of classroom talk. We present a case in which we align prosodic features with the content of teacher's talk during a nine-week physics course. This article shows that prosodic analyses may have added value for research on learning and professional development. Namely, we illustrate that acting in an authentic classroom setting might trigger specific prosodic aspects in teacher's talk. We further found indications that the teacher applied different voice prosody regarding certain patterns of classroom talk. For the future, we suggest that a combination of content and prosodic analysis is a promising tool for gaining new insights into classroom talk.