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Mass spectrometry-based sample multiplexing with isobaric tags permits the development of high-throughput and precise quantitative biological assays with proteome-wide coverage and minimal missing values. Here, we nearly doubled the multiplexing capability of the TMTpro reagent set to a 35-plex through the incorporation of one deuterium isotope into the reporter group. Substituting deuterium frequently results in suboptimal peak coelution, which can compromise the accuracy of reporter ion-based quantification. To counteract the deuterium effect on quantitation, we implemented a strategy that necessitated the segregation of nondeuterium and deuterium-containing channels into distinct subplexes during normalization procedures, with reassembly through a common bridge channel. This multiplexing strategy of “design independent sub-plexes but acquire together” (DISAT) was used to compare protein expression differences between human cell lines and in a cysteine-profiling (i.e., chemoproteomics) experiment to identify compounds binding to cysteine-113 of Pin1.

Sample multiplexing-based proteomic strategies rely on fractionation to improve proteome coverage. Tandem mass tag (TMT) experiments, for example, can currently accommodate up to 18 samples with proteins spanning several orders of magnitude, thus necessitating fractionation to achieve reasonable proteome coverage. Here, we present a simple yet effective peptide fractionation strategy that partitions a pooled TMT sample with a two-step elution using a strong anion-exchange (SAX) spin column prior to gradient-based basic pH reversed-phase (BPRP) fractionation. We highlight our strategy with a TMTpro18-plex experiment using nine diverse human cell lines in biological duplicate. We collected three data sets, one using only BPRP fractionation and two others of each SAX-partition followed by BPRP. The three data sets quantified a similar number of proteins and peptides, and the data highlight noticeable differences in the distribution of peptide charge and isoelectric point between the SAX partitions. The combined SAX partition data set contributed 10% more proteins and 20% more unique peptides that were not quantified by BPRP fractionation alone. In addition to this improved fractionation strategy, we provide an online resource of relative abundance profiles for over 11,000 proteins across the nine human cell lines, as well as two additional experiments using ovarian and pancreatic cancer cell lines.

Identifying the factors that influence student academic performance is essential to provide timely and effective support interventions. The data collected during enrolment and after commencement into a course provide an important source of information to assist with identifying potential risk indicators associated with poor academic performance and attrition. Both predictive and descriptive data mining techniques have been applied on educational data to discover the significant reasons behind student performance. These techniques have their own advantages and limitations. For example, predictive techniques tend to maximise accuracy for correctly classifying students, while the descriptive techniques simply search for interesting student features without considering their academic outcome. Subgroup discovery is a data mining method which takes the advantages of both predictive and descriptive approaches. This study uses subgroup discovery to extract significant factors of student performance for a certain outcome (Pass or Fail). In this work, we have utilised student demographic and academic data recorded at enrolment, as well as course assessment and participation data retrieved from the institution’s learning management system (Moodle) to detect the factors affecting student performance. The results have demonstrated the effectiveness of the subgroup discovery method in general in identifying the factors, and the pros and cons of some popular subgroup discovery algorithms used in this research. From the experiments, it has been found that students, who have indigent socio-economic background or been admitted based on special entry requirement, are most likely to fail. The experiments on Moodle data have revealed that students having lower level of access to the course resources and forum have higher possibility of being unsuccessful. From the combined data, we have identified some interesting subgroups which are not detected using enrolment or Moodle data separately. It has been found that those students, who study off-campus or part-time and have a low level of contributions to the course learning activities, are more likely to be the low-performing students.

ABSTRACTThis article reports on the findings of a study that investigated the effects of instructional conditions and prior experience on students’ self-reflection. The study was conducted with the use of a video annotation tool that was used by undergraduate performing arts students to reflect on their video-recorded performances. The study shows a consistent positive effect of previous experience with the video annotation tool for engagement with reflection. Graded instructional conditions with feedback had a positive effect on increasing higher order reflections particularly for students with prior experience with the video annotation tool for reflective purposes. The finding suggests that when including reflection in the curriculum, it is important to consider introducing it at a program or degree level rather than individual courses in order to provide an opportunity for students to gain experience with reflection and any particular tool that is used (e.g., a video annotation tool). Furthermore, reflective tasks should be scaffolded into the curriculum with ample opportunity for formative feedback and summative assessment in order to encourage higher order thinking and foster students’ metacognitive awareness and monitoring for increased goal-setting and acknowledgement of the motive or effect of their observed behavior.

The South Australian government has announced a trial of AI technologies in eight public high schools. The SA school trial will examine the benefits and challenges of using AI tools to support student learning. [Extracted from the article]

This paper reports on a study investigating the potential relationship between a student’s discussion forum activity and their academic performance. The study also examined the influence of the delivery method (i.e. blended or fully online) on the impact that forum participation may have on a student’s final mark. To address these aims, student forum participation data and teaching delivery method were extracted from the universities Learning Management System (LMS). The analysis identified that students who actively participate in their teaching unit’s discussion forum are more likely to achieve a higher final mark than those that do not participate. It was also observed that the resulting effect of participation in a teaching unit’s online discussion forum was greater for a blended delivery modal than for fully online teaching units. This study affirms how learning analytics data derived from online discussion forums can be proactively applied to enhance teaching and learning practice.

Providing new skills and competencies for the future workforce is one of the major tasks of lifelong learning. However, doing so will require the ongoing support of lifelong learners as they transition from old contexts to new ones, a problem that has been given far less attention. Professionals can undergo significant restructuring of their knowledge, skills, and identities as they transition between career roles, industries, and sectors. Domains such as learning analytics (LA) promise to support learners by leveraging granular data collected via technology during learning. We argue that to support transitions across lifelong learning, LA needs new analytical and methodological approaches. To enable insights, research needs to capture and explain variability, dynamics, and causal interactions between different levels of individual development, at varying time scales. Scholarly conceptions of the context in which transitions occur are also required. Our argument builds on the synthesis of interdisciplinary literature about transitions in the thematic domains such as conceptual change, shifts between educational systems, and changing roles during life course. We highlight specific areas in research designs and current analytical methodologies that hinder insight into transformational changes during transitions. The paper concludes with starting points and frameworks that can advance research in this area.