Technological and Implementation Issues in Moodle-Based Digital Badge System

Digital badges, touted as a gamification tool that can potentially influence learner motivation, engagement and participation, are being used increasingly in a variety of educational domains to facilitate and motivate learning. Using a badge system design implemented in the Moodle learning management platform, data was collected from four experiments from 2015 to 2017 to examine the effects of gamification with the use of digital badges on introductory programming students' intrinsic motivation. This paper provides an in-depth examination of seldomly discussed technological and implementation issues we encountered in implementing our Moodle-based badge system, worthy of exploration to support future gamification studies in this area. Our gamified implementation is analyzed according to five main factors primarily adopted from an IT implementation framework: (1) assessment of needs, (2) choice of technology, (3) technological infrastructure, (4) system and environmental factors and (5) evaluation. The findings highlight enabling and challenging factors associated with the technology and badge implementation. Our experience shows that badge systems may be influenced by contextual factors such as cost and scale of implementation. We provide recommendations to guide educational stakeholders, particularly those considering Moodle as their badge implementation platform

Technological and Implementation Issues in Moodle-Based Digital Badge System

Digital badges, touted as a gamification tool that can potentially influence learner motivation, engagement and participation, are being used increasingly in a variety of educational domains to facilitate and motivate learning. Using a badge system design implemented in the Moodle learning management platform, data was collected from four experiments from 2015 to 2017 to examine the effects of gamification with the use of digital badges on introductory programming students' intrinsic motivation. This paper provides an in-depth examination of seldomly discussed technological and implementation issues we encountered in implementing our Moodle-based badge system, worthy of exploration to support future gamification studies in this area. Our gamified implementation is analyzed according to five main factors primarily adopted from an IT implementation framework: (1) assessment of needs, (2) choice of technology, (3) technological infrastructure, (4) system and environmental factors and (5) evaluation. The findings highlight enabling and challenging factors associated with the technology and badge implementation. Our experience shows that badge systems may be influenced by contextual factors such as cost and scale of implementation. We provide recommendations to guide educational stakeholders, particularly those considering Moodle as their badge implementation platform

Designing and engineering evolutionary robust genetic circuits

<p>Abstract</p> <p>Background</p> <p>One problem with engineered genetic circuits in synthetic microbes is their stability over evolutionary time in the absence of selective pressure. Since design of a selective environment for maintaining function of a circuit will be unique to every circuit, general design principles are needed for engineering evolutionary robust circuits that permit the long-term study or applied use of synthetic circuits.</p> <p>Results</p> <p>We first measured the stability of two BioBrick-assembled genetic circuits propagated in <it>Escherichia coli </it>over multiple generations and the mutations that caused their loss-of-function. The first circuit, T9002, loses function in less than 20 generations and the mutation that repeatedly causes its loss-of-function is a deletion between two homologous transcriptional terminators. To measure the effect between transcriptional terminator homology levels and evolutionary stability, we re-engineered six versions of T9002 with a different transcriptional terminator at the end of the circuit. When there is no homology between terminators, the evolutionary half-life of this circuit is significantly improved over 2-fold and is independent of the expression level. Removing homology between terminators and decreasing expression level 4-fold increases the evolutionary half-life over 17-fold. The second circuit, I7101, loses function in less than 50 generations due to a deletion between repeated operator sequences in the promoter. This circuit was re-engineered with different promoters from a promoter library and using a kanamycin resistance gene (<it>kanR</it>) within the circuit to put a selective pressure on the promoter. The evolutionary stability dynamics and loss-of-function mutations in all these circuits are described. We also found that on average, evolutionary half-life exponentially decreases with increasing expression levels.</p> <p>Conclusions</p> <p>A wide variety of loss-of-function mutations are observed in BioBrick-assembled genetic circuits including point mutations, small insertions and deletions, large deletions, and insertion sequence (IS) element insertions that often occur in the scar sequence between parts. Promoter mutations are selected for more than any other biological part. Genetic circuits can be re-engineered to be more evolutionary robust with a few simple design principles: high expression of genetic circuits comes with the cost of low evolutionary stability, avoid repeated sequences, and the use of inducible promoters increases stability. Inclusion of an antibiotic resistance gene within the circuit does not ensure evolutionary stability.</p

The Synthetic Biology Open Language (SBOL) Version 3:Simplified Data Exchange for Bioengineering

The Synthetic Biology Open Language (SBOL) is a community-developed data standard that allows knowledge about biological designs to be captured using a machine-tractable, ontology-backed representation that is built using Semantic Web technologies. While early versions of SBOL focused only on the description of DNA-based components and their sub-components, SBOL can now be used to represent knowledge across multiple scales and throughout the entire synthetic biology workflow, from the specification of a single molecule or DNA fragment through to multicellular systems containing multiple interacting genetic circuits. The third major iteration of the SBOL standard, SBOL3, is an effort to streamline and simplify the underlying data model with a focus on real-world applications, based on experience from the deployment of SBOL in a variety of scientific and industrial settings. Here, we introduce the SBOL3 specification both in comparison to previous versions of SBOL and through practical examples of its use

BBF RFC 108: Synthetic Biology Open Language (SBOL) Version 2.0.0

The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, filling a need not satisfied by other pre-existing standards

Synthetic Biology Open Language (SBOL) Version 2.0.0

Synthetic biology builds upon the techniques and successes of genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. The field still faces substantial challenges, including long deve

Capturing Multicellular System Designs Using Synthetic Biology Open Language (SBOL)

8 Pág.Synthetic biology aims to develop novel biological systems and increase their reproducibility using engineering principles such as standardization and modularization. It is important that these systems can be represented and shared in a standard way to ensure they can be easily understood, reproduced, and utilized by other researchers. The Synthetic Biology Open Language (SBOL) is a data standard for sharing biological designs and information about their implementation and characterization. Previously, this standard has only been used to represent designs in systems where the same design is implemented in every cell; however, there is also much interest in multicellular systems, in which designs involve a mixture of different types of cells with differing genotype and phenotype. Here, we show how the SBOL standard can be used to represent multicellular systems, and, hence, how researchers can better share designs with the community and reliably document intended system functionality.This work was supported in part by NSF Expeditions in Computing Program Award No. 1522074 as part of the Living Computing Project and by the Defense Advanced Research Projects Agency under Contract No. W911NF-17-2-0098. The views, opinions, and/or findings expressed are of the author(s) and should not be interpreted as representing official views or policies of the Department of Defense or the U.S. Government. A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (No.EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU Grant No. 820699)Peer reviewe

In-Fusion BioBrick assembly and re-engineering

Genetic circuits can be assembled from standardized biological parts called BioBricks. Examples of BioBricks include promoters, ribosome-binding sites, coding sequences and transcriptional terminators. Standard BioBrick assembly normally involves restriction enzyme digestion and ligation of two BioBricks at a time. The method described here is an alternative assembly strategy that allows for two or more PCR-amplified BioBricks to be quickly assembled and re-engineered using the Clontech In-Fusion PCR Cloning Kit. This method allows for a large number of parallel assemblies to be performed and is a flexible way to mix and match BioBricks. In-Fusion assembly can be semi-standardized by the use of simple primer design rules that minimize the time involved in planning assembly reactions. We describe the success rate and mutation rate of In-Fusion assembled genetic circuits using various homology and primer lengths. We also demonstrate the success and flexibility of this method with six specific examples of BioBrick assembly and re-engineering. These examples include assembly of two basic parts, part swapping, a deletion, an insertion, and three-way In-Fusion assemblies

Synthetic biology open language (SBOL) version 3.0.0

Synthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, following an open community process involving both wet bench scientists and dry scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.0.0, which condenses and simplifies previous versions of SBOL based on experiences in deployment across a variety of scientific and industrial settings. In particular, SBOL 3.0.0, (1) separates sequence features from part/sub-part relationships, (2) renames Component Definition/Component to Component/Sub-Component, (3) merges Component and Module classes, (4) ensures consistency between data model and ontology terms, (5) extends the means to define and reference Sub-Components, (6) refines requirements on object URIs, (7) enables graph-based serialization, (8) moves Systems Biology Ontology (SBO) for Component types, (9) makes all sequence associations explicit, (10) makes interfaces explicit, (11) generalizes Sequence Constraints into a general structural Constraint class, and (12) expands the set of allowed constraints