How the monitoring events of individual students are associated with phases of regulation:a network analysis approach

Abstract The current study uses a within-person temporal and sequential analysis to understand individual learning processes as part of collaborative learning. Contemporary perspectives of self-regulated learning acknowledge monitoring as a crucial mechanism for each phase of the regulated learning cycle, but little is known about the function of the monitoring of these phases by individual students in groups and the role of motivation in this process. This study addresses this gap by investigating how monitoring coexists temporally and progresses sequentially during collaborative learning. Twelve high school students participated in an advanced physics course and collaborated in groups of three for twenty 90-minute learning sessions. Each student’s monitoring events were first identified from the videotaped sessions and then associated with the regulation phase. In addition, the ways in which students acknowledged each monitoring event were coded. The results showed that cyclical phases of regulation do not coexist. However, when we examinedtemporal and sequential aspects of monitoring, the results showed that the monitoring of motivation predicts the monitoring of task definition, leading to task enactment. The results suggest that motivation is embedded inregulation phases. The current study sheds light on idiographic methods that have implications for individual learning analytics

What makes an online problem-based group successful?:a learning analytics study using social network analysis

Abstract Background: Although there is a wealth of research focusing on PBL, most studies employ self-reports, surveys, and interviews as data collection methods and have an exclusive focus on students. There is little research that has studied interactivity in online PBL settings through the lens of Social Network Analysis (SNA) to explore both student and teacher factors that could help monitor and possibly proactively support PBL groups. This study adopts SNA to investigate how groups, tutors and individual student’s interactivity variables correlate with group performance and whether the interactivity variables could be used to predict group performance. Methods: We do so by analyzing 60 groups’ work in 12 courses in dental education (598 students). The interaction data were extracted from a Moodle-based online learning platform to construct the aggregate networks of each group. SNA variables were calculated at the group level, students’ level and tutor’s level. We then performed correlation tests and multiple regression analysis using SNA measures and performance data. Results: The findings demonstrate that certain interaction variables are indicative of a well-performing group; particularly the quantity of interactions, active and reciprocal interactions among students, and group cohesion measures (transitivity and reciprocity). A more dominating role for teachers may be a negative sign of group performance. Finally, a stepwise multiple regression test demonstrated that SNA centrality measures could be used to predict group performance. A significant equation was found, F (4, 55) = 49.1, p < 0.01, with an R2 of 0.76. Tutor Eigen centrality, user count, and centralization outdegree were all statistically significant and negative. However, reciprocity in the group was a positive predictor of group improvement. Conclusions: The findings of this study emphasized the importance of interactions, equal participation and inclusion of all group members, and reciprocity and group cohesion as predictors of a functioning group. Furthermore, SNA could be used to monitor online PBL groups, identify important quantitative data that helps predict and potentially support groups to function and co-regulate, which would improve the outcome of interacting groups in PBL. The information offered by SNA requires relatively little effort to analyze and could help educators get valuable insights about their groups and individual collaborators

Supporting self-regulated learning with learning analytics interventions:a systematic literature review

Abstract During the past years scholars have shown an increasing interest in supporting students' self-regulated learning (SRL). Learning analytics (LA) can be applied in various ways to identify a learner’s current state of self-regulation and support SRL processes. It is important to examine how LA has been used to identify the need for support in different phases of SRL cycle, which channels are used to mediate the intervention and how efficient and impactful the intervention is. This will help the learners to achieve the anticipated learning outcomes. The systematic literature review followed PRISMA 2020 statement to examine studies that applied LA interventions to enhance SRL. The search terms used for this research identified 753 papers in May 2021. Of these, 56 studies included the elements of LA, SRL, and intervention. The reviewed studies contained various LA interventions aimed at supporting SRL, but only 46% of them revealed a positive impact of an intervention on learning. Furthermore, only four studies reported positive effects for SRL and covered all three SRL phases (planning, performance, and reflection). Based on the findings of this literature review, the key recommendation is for all phases of SRL to be considered when planning interventions to support learning. In addition, more comparative research on this topic is needed to identify the most effective interventions and to provide further evidence on the effectiveness of interventions supporting SRL

Analyzing the effect of free stream turbulence on gaseous non-premixed flames

The effects of free stream turbulence on non-premixed flames are numerically analyzed. The Spalding eddy dissipation mathematical model is used to control the reaction rate by the large-eddy time scale. The turbulence energy production and dissipation rates are simulated by the ?-e turbulence model in order to investigate the dependence of the combustion properties on free stream turbulence. The reacting NS equations were spatially discretized and solved through a finite volume scheme and a decoupled pressure-velocity approach, respectively. The flame was assumed to be steady-state, two dimensional and axisymmetric. The reported results include the velocity, temperature and turbulent reaction rate along the flame propagation field. It is found that the increase of free stream turbulence intensity reduces the reaction zone significantly, hence, induces the flame extinction process

A person-centered approach to study students’ socio-emotional interaction profiles and regulation of collaborative learning

Abstract Emotions in collaborative learning both originate from and are externalized in students’ socio-emotional interactions, and individual group members evidently contribute to these interactions to varying degrees. Research indicates that socio-emotional interactions within a group are related with the occurrence of co- and socially shared regulation of learning, which poses a need to study individual contributions to these interactions via a person-centered approach. This study implements multimodal data (video and electrodermal activity) and sequence mining methods to explore how secondary school students’ (n = 54, 18 groups) participation in socio-emotional interactions evolved across a series of collaborative tasks. On this basis, it identifies subgroups of students with distinct longitudinal profiles. Furthermore, it investigates how students with different socio-emotional interaction profiles contributed to their groups’ regulation of learning. Three profiles were identified: negative, neutral, and diverse. Each profile represents a particular socio-emotional interaction pattern with unique characteristics regarding the emotional valence of participation and physiological emotional activation. The profiles relate to students’ contributions to group regulation of learning. Students with the diverse profile were more likely to contribute to regulation, whereas the neutral profile students were less likely to contribute. The results highlight the importance of person-centered methods to account for individual differences and participation dynamics in collaborative learning and consequently clarify how they relate to and influence group regulation of learning

Affective states and regulation of learning during socio-emotional interactions in secondary school collaborative groups

Abstract Background: Group affective states for learning are constantly formed through socio-emotional interactions. However, it remains unclear how the affective states vary during collaboration and how they occur with regulation of learning. Appropriate methods are needed to track both group affective states and these interaction processes. Aims: The present study identifies different socio-emotional interaction episodes during groups’ collaborative learning and examines how group affective states fluctuate with regulation of learning during these episodes. Sample: The participants were 54 secondary school students working in groups across four science learning sessions. Methods: Multichannel process data (video, electrodermal activity [EDA]) were collected in an authentic classroom. Groups’ affective states were measured with emotional valence captured from video data, and activation captured as sympathetic arousal from EDA data. Regulation of learning was observed from the videotaped interactions. Results: The study disclosed four clusters of socio-emotional interaction episodes (positive, negative, occasional regulation, frequent regulation), which differed in terms of fluctuation of affective states and activated regulation of learning. These clustered episodes confirm how affective states are constantly reset by socio-emotional interactions and regulation of learning. The results also show that states requiring regulation do not automatically lead to its activation. Conclusions: By advancing existing understanding of how group level socio-emotional processes contribute to regulation of learning, the study has implications for educational design and psychological practice. Methodologically, it contributes to collaborative learning research by employing multiple data channels (including biophysiological measures) to explore the various dimensions of socio-emotional processes in groups

Development of Sustained Release Baricitinib Loaded Lipid-Polymer Hybrid Nanoparticles with Improved Oral Bioavailability

Baricitinib (BTB) is an orally administered Janus kinase inhibitor, therapeutically used for the treatment of rheumatoid arthritis. Recently it has also been approved for the treatment of COVID-19 infection. In this study, four different BTB-loaded lipids (stearin)-polymer (Poly(d,l-lactide-co-glycolide)) hybrid nanoparticles (B-PLN1 to B-PLN4) were prepared by the single-step nanoprecipitation method. Next, they were characterised in terms of physicochemical properties such as particle size, zeta potential (ζP), polydispersity index (PDI), entrapment efficiency (EE) and drug loading (DL). Based on preliminary evaluation, the B-PLN4 was regarded as the optimised formulation with particle size (272 ± 7.6 nm), PDI (0.225), ζP (−36.5 ± 3.1 mV), %EE (71.6 ± 1.5%) and %DL (2.87 ± 0.42%). This formulation (B-PLN4) was further assessed concerning morphology, in vitro release, and in vivo pharmacokinetic studies in rats. The in vitro release profile exhibited a sustained release pattern well-fitted by the Korsmeyer–Peppas kinetic model (R2 = 0.879). The in vivo pharmacokinetic data showed an enhancement (2.92 times more) in bioavailability in comparison to the normal suspension of pure BTB. These data concluded that the formulated lipid-polymer hybrid nanoparticles could be a promising drug delivery option to enhance the bioavailability of BTB. Overall, this study provides a scientific basis for future studies on the entrapment efficiency of lipid-polymer hybrid systems as promising carriers for overcoming pharmacokinetic limitations

Application of CO2 Supercritical Fluid to Optimize the Solubility of Oxaprozin: Development of Novel Machine Learning Predictive Models

Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO2) for particle engineering. SCCO2 has great potential for application as a green and eco-friendly technique to reach small crystalline particles with narrow particle size distribution. In this paper, an artificial intelligence (AI) method has been used as an efficient and versatile tool to predict and consequently optimize the solubility of oxaprozin in SCCO2 systems. Three learning methods, including multi-layer perceptron (MLP), Kriging or Gaussian process regression (GPR), and k-nearest neighbors (KNN) are selected to make models on the tiny dataset. The dataset includes 32 data points with two input parameters (temperature and pressure) and one output (solubility). The optimized models were tested with standard metrics. MLP, GPR, and KNN have error rates of 2.079 × 10−8, 2.173 × 10−9, and 1.372 × 10−8, respectively, using MSE metrics. Additionally, in terms of R-squared, they have scores of 0.868, 0.997, and 0.999, respectively. The optimal inputs are the same as the maximum possible values and are paired with a solubility of 1.26 × 10−3 as an output

المهددات التي تواجه البيئة البحرية والصيد السمكي في قطاع غزة: دراسة ميدانية ومرجعية

The importance of marine resources in the Gaza Strip stems from the fact that it represents a significant source of animal protein to the Palestinians and as a source of income to the fishery sector which covers more than 2500 fishermen. Due to the small fishing area available to the Palestinians, the fishermen usually exert intensive fishing efforts using all available means to achieve abundant catches with no respect to the impacts of their activities on the marine environment and fisheries resources. The current study aims at identifying the threats facing the marine environment and fisheries resources in the Gaza Strip and at suggesting possible recommendations dealing with their progress. The factors threatening the marine environment and fishing in the Gaza Strip included untreated wastewater disposal from various sources including Wadi Gaza, multi-source solid waste disposal and alteration of the landscape of the marine coast through rock removal, shanty constructions and coastal sand dunes depletion. The weakness of fishermen infrastructure, overfishing using inappropriate means including bottom trawling and small-meshed nets, fishing using chemical pesticides, catch of threatened marine turtles and lack of efficient fishing harbors are also major threats to marine life and environment. Besides, the Israeli military aggressions and restrictions by controlling fishing areas, sea closure, poaching and arresting of fishermen and intentional destruction of fishing gear are actual threats to marine fishing and fishermen saftey. Finally, the study suggests the necessity of stopping pollution sources, improving the infrastructure of fishing sector and fishermen and improving the cooperation level among different parties to ensure better management and sustainability of the coastal and marine environment. The role of official and non-official media and educational institutions in enhancing research, respect and awareness to all stakeholders and public towards marine environment should be encouraged, elevated and put into action.تكمن أهمية الثروة السمكية في قطاع غزة في كونها تمثل أحد مصادر البروتين الحيواني الذي يحتاج إليه الفلسطينيون لتلبية احتياجاتهم الغذائية و مصدر دخل مستمر لقطاع الصيادين الذين يفوق تعدادهم الـ 2500 صياد. ونظرا لضيق المساحة البحرية المتاحة للصيد السمكي في قطـاع غزة يلجأ الصيادون إلي تكثيف جهد الصيد بكافة السبل و الوسائل للحصول على إنتاج سمكي وفير دون الاكتراث بالنواحي البيئية لهذا النشــاط على الموارد السمكية و البيئة البحرية. تهدف هذه الدراسة المسحية إلى تحديد المهددات التي تواجه البيئة البحرية و الصيد السمكي في قطاع غزة و إلى وضع مقترحات ممكنة في سبيل النهوض بهما. أظهرت الدراسة العديد من العوامل التي تعترض البيئة البحرية والصيد السمكي في قطاع غزة متمثلة بإلقاء المياه العادمة غير المعالجة من مصادر متعددة تشمل مجرى وادي غزة و بؤر التفريغ المنتشرة على طول الساحل، طرح النفايات الصلبة متعددة المصادر، تغيير تركيبة و ملامح الساحل الفلسطيني باقتلاع الصخور و بناء المنشآت العشوائية و استنزاف رمال البحر و الكثبان الرملية الساحلية مما يثبط من الوظيفة البيئية لها، ضعف البنية التحتية للصيادين، الصيد الجائر باستخدام معدات و وسائل صيد غير ملائمة مثل شباك الجر القاعي و الشباك ذات العيون الصغيرة، استعمال السموم الكيماوية في صيد الأسماك، صيد السلاحف البحرية المهددة بالاختفاء عالميا، افتقار قطاع غزة لموانئ صيد عالية الكفاءة مما يحدو بالصيادين لاستخدام رمال الشاطئ لإنزال مراكبهم في البحر و إخراجها منه مما يؤثر على العمر الإنتاجي لها. تضاف إلى ذلك كله القيود و الانتهاكات العسكرية الإسرائيلية المتمثلة بالتحكم بمناطق الصيد السمكي و إغلاق البحر أمام الصيادين و المطاردات الزورقية و الاعتقالات للصيادين و تدمير معدات الصيد و إتلافها. و في الختام، اقترحت الدراسة ضرورة وقف مصادر التلوث البحري و التعديات، و ضرورة تحسين البنية التحتية لقطاع الصيد و الصيادين، و تحسين مستوى التعاون بين المؤسسات المختلفة بما يكفل إدارة و تنمية البيئة البحرية و الساحلية بشكل مستدام، كما و تؤكد الدراسة على ضرورة تناول وسائل الإعلام الرسمي و غير الرسمي لقضايا البيئة البحرية الفلسطينية و على دور المؤسسات التعليمية في زيادة النشاط العلمي و التثقيفي و التوعوي لكافة شرائح المجتمع الفلسطيني و ضرورة افتتاح أقسام و مراكز بحوث للعلوم البحرية

Efficacy of SPG-ODN 1826 Nanovehicles in Inducing M1 Phenotype through TLR-9 Activation in Murine Alveolar J774A.1 Cells: Plausible Nano-Immunotherapy for Lung Carcinoma

Alveolar macrophages are the first line of defense against intruding pathogens and play a critical role in cancer immunology. The Toll-like receptor (TLR) family mediates an important role in recognizing and mounting an immune response against intruding microbes. TLR-9 is a member of the intracellular TLR family, which recognizes unmethylated CG motifs from the prokaryotic genome. Upon its activation, TLR-9 triggers downstream of the MyD-88-dependent transcriptional activation of NF-κB, and subsequently results in abundant inflammatory cytokines expression that induces a profound inflammatory milieu. The present exploratory investigation aimed at elucidating the potency of schizophyllan for entrapping ODN 1826 (SPG-ODN 1826)-mediated stimulation of TLR-9 in provoking an inflammatory-type response in murine alveolar macrophages. Schizophyllan (SPG), a representative of the β-glucan family, was used in the present study as a nanovehicle for endosomal trafficking of CpG ODN 1826. TEM analysis of SPG-ODN 1826 nanovehicles revealed that the prepared nanovehicles are spherical and have an average size of about 100 nm. Interestingly, SPG-ODN 1826 nanovehicles were competent in delivering their therapeutic payload within endosomes of murine alveolar macrophage (J774A.1) cells. Exposure of these nanovehicles within LPS stimulated J774A.1, resulted in a significant provocation of reactive oxygen species (ROS) (p < 0.01) in comparison to CpG ODN 1826 alone. Moreover, the formulated nanovehicles succeeded in generating a profound Th1-based cytokine profile constituted by enhanced expression of IFN-γ (p < 0.001) and IL-1β (p < 0.001) inflammatory cytokines. These findings clearly indicated the immunostimulatory potential of SPG-ODN 1826 nanovehicles for inducing the Th1-type phenotype, which would certainly assist in skewing M2 phenotype into the much-desired M1 type during lung cancer