The Virtual Tutor: Combining Conversational Agents with Learning Analytics to support Formative Assessment in Online Collaborative Learning

The objective of this design science research project is to combine Learning Analytics data with a conversational agent communication interface, the Virtual Tutor, which is able to support formative assessment for educators and learners in online collaborative learning (OCL) environments. The main benefit for educators is providing user-adaptable Learning Analytics data requests to fit the information needs for formative assessment. Learners receive semi-automated feedback on their platform activity in form of reports, which shall trigger self-reflection processes. By extracting requirements from the potential users and deriving design principles, a conversational agent is implemented and evaluated in an online collaborative learning course. The results indicate that the Virtual Tutor reduces the task load of educators, supports formative assessment and gives scaffolded guidance to the learners by reflecting their performance, thus triggering self-reflection processes. This research provides a first step towards data supported (semi-)automated feedback systems for formative assessment in OCL courses

OER meets COL: Learning about collaborative online learning with OER

... The design of advanced blended learning arrangements demands a shift of focus from mere content-based knowledge delivery to moderated interactions between topics, peers and educators. The provision of suitable learning content does not serve primarily as learning resources, but rather as a trigger for active learning as an appropriate combination of individual and collaborative engagement to achieve learning goals which address the higher levels of Bloom’s taxonomy. This triggered interaction benefits strongly by demand-driven and goal-oriented tele-tutorial moderation, perhaps based on deeper insight into learners’ interactions, provided by Learning Analytics. [Aus: Collaborative Online Learning

The Virtual Tutor: Tasks for conversational agents in Online Collaborative Learning Environments

Online collaborative learning environments are becoming increasingly popular in higher education. E-tutors need to supervise, guide students and look out for conflicts within the online environment to ensure a successful learning experience. Web-based platforms allow for interactive elements such as conversational agents to disencumber the e-tutor. Repeatable tasks, which do not require a human response, can be automatized by these systems. The aim of this study is to identify and synthesize the tasks an e-tutor has and to investigate the automatisation potential with conversational agents. Using a design science research approach a literature review is conducted, identifying 13 tasks. Subsequently, a matrix is established, contrasting the tasks with requirements for the use of conversational agents. Furthermore, a virtual tutor framework is developed, clarifying the agent type selection, the technical structure and components for a prototype development in an online collaborative learning environment

First shotgun metagenomics study of Juan de Fuca deep-sea sediments reveals distinct microbial communities above, within, between, and below sulfate methane transition zones

The marine deep subsurface is home to a vast microbial ecosystem, affecting biogeochemical cycles on a global scale. One of the better-studied deep biospheres is the Juan de Fuca (JdF) Ridge, where hydrothermal fluid introduces oxidants into the sediment from below, resulting in two sulfate methane transition zones (SMTZs). In this study, we present the first shotgun metagenomics study of unamplified DNA from sediment samples from different depths in this stratified environment. Bioinformatic analyses showed a shift from a heterotrophic, Chloroflexota-dominated community above the upper SMTZ to a chemolithoautotrophic Proteobacteria-dominated community below the secondary SMTZ. The reintroduction of sulfate likely enables respiration and boosts active cells that oxidize acetate, iron, and complex carbohydrates to degrade dead biomass in this low-abundance, low-diversity environment. In addition, analyses showed many proteins of unknown function as well as novel metagenome-assembled genomes (MAGs). The study provides new insights into microbial communities in this habitat, enabled by an improved DNA extraction protocol that allows a less biased view of taxonomic composition and metabolic activities, as well as uncovering novel taxa. Our approach presents the first successful attempt at unamplified shotgun sequencing samples from beyond 50 meters below the seafloor and opens new ways for capturing the true diversity and functional potential of deep-sea sediments

Recommendations for the Selection of Methods for the Analysis of eCollaboration based on a Systematic Literature Review

Learning Analytics plays an increasing role in the analysis of virtual learning activities. This article addresses the gap between educational needs and technical supply. By means of a Systematic Literature Review of the LAK conferences the authors extracted observations, methods and tools which represent potential solutions for a given eCollaboration scenario. Based on three prioritised examples of an observation sheet, methods are derived and recommendations for the use of Learning Analytics tools are given. The result is a catalogue that enable users to select suitable methods and tools for an implementation. The (semi-) automation can increase the efficiency of Community Managers in monitoring the participants and hence make real-time intervention feasible

Digitalisation in Higher Education: A Flipped Classroom Arrangement to foster Internationalisation

This practical paper presents a successful international teaching & learning project in Higher Education (HE), which can be used as blue print for similar international HE teaching/learning cooperations. A virtual module, delivering 5 ECTS to participants from Germany and Iran, was organized as flipped classroom (FC), consisting of 2 phases: (1) online phase of 7 weeks, having started at April 12, 2019, with 15 students from Shiraz University, Iran, and 23 students from TU Dresden, Germany, collaborating in mixed teams of 5–6 participants each on a complex business case under tight guidance by qualified learning community managers, and (2) a follow-up on-site meeting at TU Dresden in the first week of July with 3 intensive workshops applying different techniques to consolidate the prior online collaboration results

Macroporous Silicone Chips for Decoding Microbial Dark Matter in Environmental Microbiomes

Natural evolution has produced an almost infinite variety of microorganisms that can colonize almost any conceivable habitat. Since the vast majority of these microbial consortia are still unknown, there is a great need to elucidate this “microbial dark matter” (MDM) to enable exploitation in biotechnology. We report the fabrication and application of a novel device that integrates a matrix of macroporous elastomeric silicone foam (MESIF) into an easily fabricated and scalable chip design that can be used for decoding MDM in environmental microbiomes. Technical validation, performed with the model organism Escherichia coli expressing a fluorescent protein, showed that this low-cost, bioinert, and widely modifiable chip is rapidly colonized by microorganisms. The biological potential of the chip was then illustrated through targeted sampling and enrichment of microbiomes in a variety of habitats ranging from wet, turbulent moving bed biofilters and wastewater treatment plants to dry air-based environments. Sequencing analyses consistently showed that MESIF chips are not only suitable for sampling with high robustness but also that the material can be used to detect a broad cross section of microorganisms present in the habitat in a short time span of a few days. For example, results from the biofilter habitat showed efficient enrichment of microorganisms belonging to the enigmatic Candidate Phyla Radiation, which comprise ∼70% of the MDM. From dry air, the MESIF chip was able to enrich a variety of members of Actinobacteriota, which is known to produce specific secondary metabolites. Targeted sampling from a wastewater treatment plant where the herbicide glyphosate was added to the chip’s reservoir resulted in enrichment of Cyanobacteria and Desulfobacteria, previously associated with glyphosate degradation. These initial case studies suggest that this chip is very well suited for the systematic study of MDM and opens opportunities for the cultivation of previously unculturable microorganisms

Conquering the Jet Lag Era: Experiences from Virtual Interdisciplinary Collaboration across Continents

Mit der Ausschreibung International Virtual Academic Collaboration (IVAC) verfolgt der Förderträger DAAD die Ziele, die Studienangebote an deutschen Hochschulen und deren ausländischen Kooperationshochschulen zu flexibilisieren und den Studierenden einen erweiterten Zugang zur internationalen Hochschulbildung zu ermöglichen. In dem geförderten Projekt Collaborative International, Intercultural & Interdisciplinary Learning (COIIIL) zwischen den Partnerinstitutionen Technische Universität Dresden, Stellenbosch University, Shiraz University und Bucknell University wurden diese Ziele adressiert