Conversational Framework Research Articles

A fusion of research-informed teaching and teaching-informed research: Designing a scalable online ecosystem for new partnerships in educational research

This paper examines the unbundling of research in the context of the Teachers’ Research Exchange (T-REX) platform, the national flagship Internet platform in Ireland for teachers to access, use and engage in research. This paper draws on two theoretical frameworks: Laurillard’s conversational framework and Salmon’s five-stage model. The first highlights the experimental, exploratory and creative aspects of developing an overall framework to structure the digital learning environment for teachers-as-researchers. The second explores the future of higher education and systems like T-REX in the era of digital transformation and the emerging context of Education 4.0. The original contribution is the integration of these frameworks in the creation of an open and shared learning platform so that schools and teachers can be supported to access, collaborate in and undertake research. In particular, the paper outlines signature features of the T-REX design and the way it has emerged over the last 5 years as an innovative platform to mediate the fusion of research and teaching in education. The paper highlights key issues and challenges in unbundling the traditional university, particularly in the context of educational research, but also the imperative of doing so, in the emerging era of Education 4.0.
 Implications for practice or policy:
 
 Supporting teachers’ research engagement is increasingly identified as a key priority in the improvement of educational standards and systems.
 T-REX is of value to educationalists interested in a shared learning and open online teacher-research platform.
 There should be a dialogic approach to the relationship between teaching and research, where each informs and enhances the other.

Mentoring PhD students working in industry: Using hermeneutics as a critical approach to the experience

While there is abundant research looking at the impact of mentoring in academic environments, inquiry into and the construction of knowledge from the experience of mentors has remained limited. This is mainly because of the methodological difficulty that is inherent in the study of mentoring experiences. The authors address this difficulty by using hermeneutics as a research method, and developing a learning framework based on the Laurillard conversational framework to reflect on a mentor’s journey throughout her experience of mentoring a group of PhD students working in industry. From this we learn that mentoring working PhDs is a common goal focused learning partnership between all actors involved. This partnership is defined by the actors and the forms of interaction within the partnership, and is enabled by the mentor’s availability and capabilities. The paper also demonstrates how hermeneutics can be used as a robust research method to study the many subjective meanings of professional mentoring – meanings that are challenging to translate into transferable knowledge for ourselves and others to learn from. In particular, the authors wish to encourage colleagues and readers to use hermeneutics as a critical approach to explore complex, human-made academic–industrial collaborative mentoring practices from different perspectives and to produce a new understanding of the potential of alternative academic–industrial collaboration links.

Creating healthy places with the Place Standard Tool – An introduction

Abstract This presentation will give an overview of the evidence around 'place' - the social AND physical environment - and how it impacts on lifelong health and wellbeing and health inequalities. It will provide a comprehensive introduction to the innovative Place Standard tool (PST) developed in partnership in Scotland - and how it translates complex health and place-making relationships into a simple set of questions. The resulting tool allows participants to identify strengths and weaknesses and begin to develop a shared understanding of place from which to take collaborative action to improve places and the lives of the people that use them. It will give a practical guide to how, when and where the PST can be deployed to support the delivery of healthy and equitable places, illustrated by real-life examples of use in a range of scales and contexts by the public sector and by communities across Scotland (and beyond) since its launch in 2015. It will also draw out the lessons learned during the first phase deployment and showcase the resultant versions that have been developed by the Scottish team to address identified gaps in a changing climate. These new versions, which will be launched in 2020, are: improvements to the main PST intended amongst other things to better enable place-based conversations to address health impacts of climate change; versions for children to support children's rights and participation; and a Design version aimed at architects and planners to support the design process to deliver healthier places. Key messages The Place Standard tool is adaptable, easy-to-use and distils complex health evidence into simple questions relevant to a range of scales and types of real-life 'place'. As a practical, accessible framework for place-based conversations to support communities and agencies to together identify priorities for action to deliver high quality, sustainable places, it has proved highly transferable to a variety of contexts and countries.

Filtering Super-Resolution Scan Conversion of Medical Ultrasound Frames

In this paper, we consider a challenging problem of reconstruction of high resolution (HR) B-mode ultrasound (US) image by proposing a novel multi-frame based super-resolution (SR) scan conversion framework. This new framework of SR scan conversion reconstructs an improved HR frame by using the scan data of several low resolution (LR) frames. It also unifies the speckle reduction and HR scan conversion in such a way that it has become a single operation to generate a super-resolved image with lesser loss of information. We evaluated the performance of the proposed model on synthetic images, ultrasound simulated (by Field II software) images and real ultrasound image dataset and the comparison is performed against some of the publicly available state-of-the-art ultrasound image enhancement techniques. Significant improvement in image quality has been achieved due to utilization of non-redundant information present in the scan data of the LR frames. We demonstrate the improvement of the proposed technique through the computation of perceptual and quantitative quality metrics, such as, SSIM, PSNR etc. over the recent competing methods.

Water-stable Mn-based MOF nanosheet as robust visible-light-responsive photocatalyst in aqueous solution

Development of visible-light-responsive metal-organic frameworks (MOFs) for promising solar energy conversion has inspired continuous interest, but it still suffers from poor stability especially in aqueous solution and/or under photoirradiation due to their relatively labile coordination bonds. Herein, a new synthesized layered Mn-based MOF (Mn-TBAPy-BK) and its exfoliated two-demensional nanosheets (Mn-TBAPy-NS) are revealed to be highly stable no matter in aqueous solution with wide pH region or under visible light irradiation. As expected, the exfoliated Mn-TBAPy-NS exhibits enhanced surface area, shortened charge transfer distance, and superior charge separation with respect to the bulk one. Moreover, the as-obtained nanosheets can be employed as effective building block for nanocomposite and heterostructure assembly to further promote charge separation as well as solar hydrogen production from aqueous solution under visible light. The finding of water stable MOF nanosheet under visible light demonstrates its promising future for solar energy conversion.

Enhancing Students’ Collaborative Learning Experiences with Laurillard’s Conversational Framework

Collaborative learning (CL) is becoming increasingly recognised as a popular pedagogical practice in higher education that promotes socialization and learning among students. However, the use of collaborative learning does risk placing too much responsibility on the learner and reducing face-to-face interaction with the educator. Therefore, there is a need for educators to find a balance in the interaction and engagement with students to help improve their perceived collaborative learning experiences.

Designing Lesson Plans For Adaptive Learning Using Moodle LMS Platform

This paper presents a research study in developing lesson plans for differentiated learning or adaptive learning using "lesson" on Moodle LMS platform. The lesson are to provide learning paths based on inquiring category from Laurillard Conversational Framework. The design of various learning paths provide teaching methods used in class such as videos, quizzes and reading tasks. This lesson when planned using flowcharts would guide the instructors to link the topics and assessment in any order that would promote students' self-paced and self-learning experience.

Porous nitrogen-rich covalent organic framework for capture and conversion of CO2 at atmospheric pressure conditions

Abstract A porous nitrogen-rich imine-linked covalent organic framework (COF1) has been synthesized by Schiff-base condensation reaction of 4,4′-azodianiline (AZO) and benzene-1, 3, 5-tricarboxaldehyde (BTA) under solvothermal conditions and characterized by various techniques. Owing to the presence of basic imine (-C N) and -azo (-N N) functionalized 1D channels, COF1 exhibits high affinity for CO2 with high isosteric heat of adsorption (Qst) value of 32.3 kJ/mol. Further, the COF1 supported ZnBr2 acts as an excellent recyclable catalyst for cycloaddition of CO2 to epoxides resulting in cyclic carbonates with high yield and 100% selectivity under solvent-free mild conditions of 1 bar of CO2. Further, the coordination of Zn(II) to basic –C N group was supported by XPS studies and theoretical calculations. Interestingly, COF1 shows excellent recyclability and can be recycled for several cycles without substantial loss of catalytic activity and structural rigidity. The high CO2 affinity combined with excellent thermal stability and catalytic activity make COF1 a promising candidate material for efficient fixation of carbon dioxide.

Catalytic Mechanisms of Zirconium-Containing Active Sites over the SBA-15 Zeolite Framework for Xylose Conversion to Methyl Lactate

Zr-containing SBA-15 zeolite (Zr-SBA-15) catalysts show good catalytic performance toward xylose conversion to methyl lactate (ML). Here, we report our study on the catalytic mechanisms for the con...

Capital configurations and trade-offs: How do families with children, wishing to move to a rural area, search for their new location in order to achieve desired forms of capital?

Since the 1970s, the concept of counterurbanization has been used within geographical and rural studies to denote the demographic revival and growth of rural areas. However, little is known about how contemporary urban-to-rural migrants actually search for their future residence. This is unfortunate, as the increased use of internet search tools may become a crucial facilitator for significant counterurbanization by providing families key information about hitherto ‘forgotten’ places where they can, better than in the larger cities, achieve the specific stocks, or ‘configurations’, of social, cultural and economic capital they desire. Therefore, drawing on Contextual Inquiry based, semi-structured interviews with 8 Danish families in various parts of Denmark in spring 2018, the purpose is to shed more light on how families with children in practice use what we term information capital , i.e. online and offline search strategies, in order to find their ideal rural place to live. In this way, information capital becomes a kind of ‘auxiliary’ capital, which allows various types of families to identify and achieve exactly the configurations of capital they desire and, by this, increase their life quality. Within a dynamic, Bourdieusian capital conversion framework, the paper shows how the families must ‘sacrifice’ capital in order to achieve desired forms of capital, that is, make trade off between various forms of capital, as for example trading off economic for social capital. • Urban-to-rural migrant families can be divided into three ideal types: Relation, Practical and Practical-Relation families. • Trade-off strategies: In relation to relocation, families traded off some forms of capital for others, e.g. economic for social. • Internet search tools should be seen as an important facilitator for counterurbanization. • In their search for a new rural location, both online and offline information capital became crucial for all families.

Palladium(II) Immobilized on Metal-Organic Frameworks for Catalytic Conversion of Carbon Dioxide to Formate.

In this work, we report the design of a two-dimensional (2D) isostructural metal-organic framework containing Pd(II) active sites, using a bipyridyl dicarboxylate linker (Mg(bpdc)(DMF)2PdCl2]n (Pd@Mg:JMS-2) and [Mn(bpdc)(DMF)2PdCl2]n(Pd@Mn:JMS-2)). The activated MOFs Pd@Mg:JMS-2a and Pd@Mn:JMS-2a were evaluated as heterogeneous catalysts for the hydrogenation of carbon dioxide (CO2) to formate. Under optimal conditions, the MOFs exhibited impressive catalytic activity with formate turnover numbers of 7272 and 9808 for Pd@Mg:JMS-2a and Pd@Mn:JMS-2a, respectively, after 24 h. These catalysts exhibited higher catalytic activity when compared to its homogeneous counterpart that was used as a linker during MOF synthesis. Post-experimental characterization showed that the structural integrity of the MOFs was not altered after catalysis. This work demonstrates that the catalytic activity of homogeneous systems can be enhanced under heterogeneous conditions by anchoring them on MOFs.

Vowels and Prosody Contribution in Neural Network Based Voice Conversion Algorithm with Noisy Training Data

This research presents a neural network based voice conversion model. While it is a known fact that voiced sounds and prosody are the most important component of the voice conversion framework, what is not known is their objective contributions particularly in a noisy and uncontrolled environment. This model uses a 3 layer feedforward neural network to map the Linear prediction analysis coefficients of a source speaker to the acoustic vector space of the target speaker with a view to objectively determine the contributions of the voiced, unvoiced and supra-segmental components of sounds to the voice conversion model. Results showed that vowels “a”, “i”, “o” have the most significant contribution in the conversion success. The voiceless sounds were also found to be most affected by the noisy training data. An average noise level of 40 dB above the noise floor were found to degrade the voice conversion success by 55.14 percent relative to the voiced sounds. The result also show that for cross-gender voice conversion, prosody conversion is more significant in scenarios where a female is the target speaker.

Vowels and Prosody Contribution in Neural Network Based Voice Conversion Algorithm with Noisy Training Data

This research presents a neural network based voice conversion model. While it is a known fact that voiced sounds and prosody are the most important component of the voice conversion framework, what is not known is their objective contributions particularly in a noisy and uncontrolled environment. This model uses a 3 layer feedforward neural network to map the Linear prediction analysis coefficients of a source speaker to the acoustic vector space of the target speaker with a view to objectively determine the contributions of the voiced, unvoiced and supra-segmental components of sounds to the voice conversion model. Results showed that vowels “a”, “i”, “o” have the most significant contribution in the conversion success. The voiceless sounds were also found to be most affected by the noisy training data. An average noise level of 40 dB above the noise floor were found to degrade the voice conversion success by 55.14 percent relative to the voiced sounds. The result also show that for cross-gender voice conversion, prosody conversion is more significant in scenarios where a female is the target speaker.

Google forms can stimulate conversations in discussion-based seminars? An activity theory perspective

One challenge in seminar-style postgraduate courses is that some students are uncomfortable with discussing course content and concepts among their peers and in front of the lecturer in seminars. This article is a case study of the incorporation of Google Form questions into seminars in a postgraduate Economic History course, a tool intervention undertaken as a response to the challenge of some students’ seminar reticence. The study explores whether the tool intervention can from students’ perspectives stimulate conversation, and examines whether the objectives of the students and the lecturer were aligned in the learning activity. The article draws on two theories to frame the research: Engeström’s (2001) third generation Activity Theory, employed to locate change-enabling contradictions and the objects of the educational activity, and Laurillard’s (2002) Conversational Framework as a theory of learning wherein students and the teacher interface with mutually accessible concepts. The study draws on interview data from structured interviews with students at the end of the course. The article contends that Google Forms are assistive in stimulating conversations around core concepts, and that a quaternary contradiction emerged between the lecturer and the individual student’s objects in the educational activity

Perturb and Observe Algorithm in Maximum Power Point Tracking (MPPT) for Solar Generation

The photovoltaic system is one of the promising sustainable power source advancements. In spite of the fact that the energy conversion productivity of the framework is still low, it has the preferred position that the operating cost is free. MPPT-Maximum power point tracking is a critical part of photovoltaic frameworks. Solar energy based vitality is viewed as one of the significant sources of sustainable power source, accessible in abundance and furthermore free of cost. Solar based photovoltaic cells are utilized to change over solar-based energy into unregulated electrical energy. These solar oriented photovoltaic cells show nonlinear qualities and give low productivity. In this method, it gets basic to extricate maximum power from solar oriented photovoltaic cells utilizing MPPT. This paper proposes P&O algorithm for refining the proficiency of the single-stage grid-associated power conversion framework. Further, this paper recommends a coordinated controller that is utilized to progress the nature of the power supply to the grid.

Symptom relief and palliative care in gynecologic oncology.

Patients with gynecologic malignancies experience varied and often difficult-to-manage symptoms through their disease course, along with decisions surrounding preferences for advance care planning. This review focuses on evidence-based symptom management for these patients and offers a framework for conversations regarding goals of therapy. There is increasing literature on palliative care specifically in gynecologic oncology, including barriers and possible solutions for early palliative care use, along with updated guidelines on postoperative pain management and tools for communication. Integration of early palliative care and focus on symptom management is an important and multidisciplinary approach to help patients with gynecologic malignancies.

Triphenylamine-based covalent imine framework for CO2 capture and catalytic conversion into cyclic carbonates

Abstract A series of covalent imine framework (CIF) comprised of triphenylamine (TPA) and triazine (T) moieties were synthesized under reflux and solvothermal conditions using different solvents: TPA-TCIF(DMF), TPA-TCIF(DM), and TPA-TCIF(BD) (DMF = dimethylformamide, DM = 1,4-dioxane:mesitylene mixture, and BD = 1-butanol:o-dichlorobenzene mixture). While TPA-TCIF(DM) and TPA-TCIF(DMF) were partially crystalline and amorphous, respectively, with a surface area of 935 and 388 m2 g−1, highly crystalline TPA-TCIF(BD) was formed with a surface area of 2907 m2 g−1 and high nitrogen content. TPA-TCIF(BD) showed a reasonable CO2 capture capacity of 77.3/50.2 mg g−1 at 1 bar and CO2 selectivity over N2 of 51.6/61.8 at 273/298 K, respectively. Subsequently, TPA-TCIF(BD) was used as catalyst support to anchor M2+ (Zn2+ and Co2+) ions for CO2 cycloaddition to various epoxides. The M2+-complexed catalysts with n-Bu4NBr showed an excellent catalytic activity with high selectivity to cyclic carbonates under mild reaction conditions. Zn/TPA-TCIF(BD) exhibited somewhat higher catalytic activity than Co/TPA-TCIF(BD), and the activity was maintained after five recycle runs.

A conceptual model for integrating affordances of mobile technologies into task-based language teaching

ABSTRACT Due to a range of different affordances, mobile technologies can be used pedagogically for language teaching and learning. However, the connection of technology to education needs to be grounded in theoretical frameworks and methodological principles. Task-based language teaching (TBLT), as an optimal approach to language teaching and learning, provides rationale and methodological principles for the application of mobile technologies. The Conversational Framework (Laurillard, D. (2007). Pedagogical forms for mobile learning: framing research questions. In N. Pachler (Ed.), Mobile learning: towards a research agenda (pp. 153–175). London: UCL university.), on the other hand, can be adapted as a framework for the design of learning process as well as for the test of affordances of mobile technologies. Based on these components, a conceptual model for integrating affordances of mobile technologies into TBLT is proposed in this study. Such a model will serve practice as well as research on the educational uses of mobile technologies in the domain of language teaching and learning. Specific procedures for the implementation of the model are illustrated and demands for teachers as well as students are discussed.

Emotional Voice Conversion Using a Hybrid Framework With Speaker-Adaptive DNN and Particle-Swarm-Optimized Neural Network

We propose a hybrid network-based learning framework for speaker-adaptive vocal emotion conversion, tested on three different datasets (languages), namely, EmoDB (German), IITKGP (Telugu), and SAVEE (English). The optimized learning model introduced is unique because of its ability to synthesize emotional speech with an acceptable perceptive quality while preserving speaker characteristics. The multilingual model is extremely beneficial in scenarios wherein emotional training data from a specific target speaker are sparsely available. The proposed model uses speaker-normalized mel-generalized cepstral coefficients for spectral training with data adaptation using the seed data from the target speaker. The fundamental frequency (F0) is transformed using a wavelet synchrosqueezed transform prior to mapping to obtain a sharpened time-frequency representation. Moreover, a feedforward artificial neural network, together with particle swarm optimization, was used for F0 training. Additionally, static-intensity modification was also performed for each test utterance. Using the framework, we were able to capture the spectral and pitch contour variabilities of emotional expression better than with other state-of-the-art methods used in this study. Considering the overall performance scores across datasets, an average melcepstral distortion (MCD) of 4.98 and root mean square error (RMSE-F0) of 10.67 were obtained in objective evaluations, and an average comparative mean opinion score (CMOS) of 3.57 and speaker similarity score of 3.70 were obtained for the proposed framework. Particularly, the best MCD of 4.09 (EmoDB-happiness) and RMSE-F0 of 9.00 (EmoDB-anger) were obtained, along with the maximum CMOS of 3.7 and speaker similarity of 4.6, thereby highlighting the effectiveness of the hybrid network model.

Metal-organic frameworks for the energy-related conversion of CO2 into cyclic carbonates.

Excessive emissions of carbon dioxide (CO2) in the atmosphere result in a series of energy and environmental issues all around the word. Thus, it is urgent to prepare efficient materials for the conversion of CO2 as a C1 source into energy-related chemical products. Porous metal-organic frameworks (MOFs) are a class of rapidly growing crystalline materials, which have attracted significant attention for application in the conversion of CO2 into cyclic carbonates. In this review article, the developments made in recent years with respect to the application of MOFs as heterogeneous catalysts for the energy-related conversion of CO2 into cyclic carbonates are highlighted; moreover, we have further discussed the opportunities and challenges in the use of MOFs in this field.