Academic literature on the topic 'Guided discovery'

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Journal articles on the topic "Guided discovery"

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Overholser, James C. "Guided Discovery." Journal of Contemporary Psychotherapy 43, no. 2 (November 27, 2012): 73–82. http://dx.doi.org/10.1007/s10879-012-9229-1.

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Nugroho, Anwari Adi, and Singgih Subiyantoro. "INTEGRASI PEMBELAJARAN GUIDED DISCOVERY DALAM MODUL SPERMATOPHYTA UNTUK MAHASISWA PENDIDIKAN BIOLOGI." Jurnal Pendidikan Matematika dan IPA 9, no. 1 (January 18, 2018): 57. http://dx.doi.org/10.26418/jpmipa.v9i1.23698.

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Guided discovery learning is a learning that invites students to actively discover the concept / knowledge through a series of activities. Guided discovery learning can be integrated in teaching modules to make learning more effective and self-reliant. This study aimed to integrate guided discovery learning in spermatophyta module for biology education students. This research is an explorative research with stages include curriculum analysis, subject matter analysis, learning model analysis, and integration of learning model in the Module. Data source in the form of book document, expert opinion, and spermatophyta module. Data analysis used qualitative descriptive analysis. Based on the analysis result, it is found that guided discovery guided discovery integrated in module include stimulation, problem statement, data collection, verification, generalization . The guided discovery guided synthesis is integrated into 3 subspaces on spermatophyta material 1) classification, determination, and nomenclature of plants, 2) spermatophyta (seed plants); 3) high plant herbarium. Integration of guided discovery learning on unified modules integrated in the module component of learning activities.Keywords: Guided discovery, Spermatophyta Module
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Gawron, Jean M., Alex Dodge, Ming-Hsiang Tsou, Brian Spitzberg, and Li An. "Linguistically guided community discovery." Big Data & Society 6, no. 1 (January 2019): 205395171984663. http://dx.doi.org/10.1177/2053951719846634.

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Within some online communities, discussion often centers on issues on which writers take sides, and within some subset of those debate-prone communities, we find over time that particular sets of writers almost always end up on the same side of an issue. These sets we call factions. In this paper, we describe a tool to perform what we call faction discovery on online communities. Generalizing methods developed in the bibliometrics and information retrieval literature, we define a network determined by similarities of content in a community of users and add in direct evidence of online ties between users (e.g., link information such as mention-links). We then perform community detection on the network to find factions. Using a set of data collected from science and fantasy blogs, we show that the discovered factions accurately reflect an active conflict in the community leading to significant, politically related social fracture.
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Asyari, Dian Noer. "KEEFEKTIFAN MODEL GUIDED DISCOVERY LEARNING UNTUK MENINGKATKAN KETERAMPILAN KETERAMPILAN BERPIKIR KRITIS." Edupedia 3, no. 2 (January 8, 2019): 17–27. http://dx.doi.org/10.35316/edupedia.v3i2.257.

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Discovery learning is a learning situation on wich the principle content of what is tobe learned is not give but must be independly discovered by student. The effectiveness of guided discovery learning model to improve students’ critical thinking skills uses 6 indicators, are: formulating problems, formulating hypotheses, analyzing date, providing alternatives, summing up, communicating and applying principle. The guided discovery learning model was included in the effective category in terms of: (a) Improvement (N-gain) of students’ critical thinking skills by 0.65 with moderate criteria and (b) Students respond positively to learning using guided discovery learning model and its learning tools on implementation.
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Turkcapar, M., Melis Kahraman, and A. Sargin. "Guided Discovery with Socratic Questioning." Journal of Cognitive-Behavioral Psychotherapy and Research 4, no. 1 (2015): 47. http://dx.doi.org/10.5455/jcbpr.188198.

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Achoy Solano, Daniela. "Implementing Guided-Discovery Grammar Learning." LETRAS, no. 68 (July 6, 2020): 143–73. http://dx.doi.org/10.15359/rl.2-68.6.

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This inquiry explores the implementation of guided discovery as a means to promote analyzing and reasoning skills in the study of grammar in the English as a Foreign Language (EFL) class. A grammar guided discovery learning-based action plan was analyzed based. This study acknowledges the need to develop analytical and reasoning skills when learning grammar and highlights therelevance of reflecting upon current teaching practices to attain effective grammar learning.
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Fitriani, Veta, and Lusi Eka Afri. "Pengembangan Lembar Kerja Siswa Matematika Berbasis Penemuan Terbimbing Untuk Siswa Kelas VII Sekolah Menengah Pertama Pada Materi Segiempat." Jurnal Absis : Jurnal Pendidikan Matematika dan Matematika 3, no. 1 (October 31, 2020): 220–29. http://dx.doi.org/10.30606/absis.v3i1.494.

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This study aims to produce valid guided discovery-based math worksheets on rectangular material. This type of research is development research. This research consists of three stages of development, definition, design, and development. This study's subjects were class VII students of SMP Negeri 3 Rambah Hilir in the second semester of the 2019/ 2020 school year. The instrument used in this study was a validation questionnaire sheet. Discovery-based worksheets guide the results of this study. Based on the validity test of the guided discovery-based student worksheet carried out on three validators with several revisions and improvements, the average score of the guided discovery-based student worksheet validation was 3.73 with a very valid category. So it can be concluded that guided discovery-based worksheets are very valid.
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Wyss, Daniel F. "Structure-guided applications in drug discovery." Drug Discovery Today 8, no. 20 (October 2003): 924–26. http://dx.doi.org/10.1016/s1359-6446(03)02853-8.

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Bindel, Thomas H., and John C. Fochi. "Guided Discovery: Law of Specific Heats." Journal of Chemical Education 74, no. 8 (August 1997): 955. http://dx.doi.org/10.1021/ed074p955.

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Flemming, Alexandra. "Resistance-guided discovery of new antibiotics." Nature Reviews Drug Discovery 12, no. 11 (October 18, 2013): 826. http://dx.doi.org/10.1038/nrd4158.

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Dissertations / Theses on the topic "Guided discovery"

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Rungta, Neha S. "Improving error discovery using guided model checking /." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1555.pdf.

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Rungta, Neha Shyam. "Improving Error Discovery Using Guided Model Checking." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/782.

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State exploration in directed software model checking is guided using a heuristic function to move states near errors to the front of the search queue. Distance heuristic functions rank states based on the number of transitions needed to move the current program state into an error location. Lack of calling context information causes the heuristic function to underestimate the true distance to the error; however, inlining functions at call sites in the control flow graph to capture calling context leads to exponential growth in the computation. This paper presents a new algorithm that implicitly inlines functions at call sites to compute distance data with unbounded calling context that is polynomial in the number of nodes in the control flow graph. The new algorithm propagates distance data through call sites during a depth-first traversal of the program. We show in a series of benchmark examples that the new heuristic function with unbounded distance data is more efficient than the same heuristic function that inlines functions up to a certain depth.
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Atkinson-Abutridy, John A. "Semantically-guided evolutionary knowledge discovery from texts." Thesis, University of Edinburgh, 2003. http://hdl.handle.net/1842/27800.

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This thesis proposes a new approach for structured knowledge discovery from texts which considers both the mining process itself, the evaluation of this knowledge by the model, and the human assessment of the quality of the outcome. This is achieved by integrating Natural-Language technology and Genetic Algorithms to produce explanatory novel hypotheses. Natural-Language techniques are specifically used to extract genre-based information from text documents. Additional semantic and rhetorical information for generating training data and for feeding a semi-structured Latent Semantic Analysis process is also captured. The discovery process is modelled by a semantically-guided Genetic Algorithm which uses training data to guide the search and optimization process. A number of novel criteria to evaluate the quality of the new knowledge is proposed. Consequently, new genetic operations suitable for text mining are designed, and techniques for Evolutionary Multi-Objective Optimization are adapted for the model to trade off between different criteria in the hypotheses.
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Rungta, Neha Shyam. "Guided Testing for Automatic Error Discovery in Concurrent Software." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3175.pdf.

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Hedden, Chet. "A guided exploration model of problem-solving discovery learning /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/7683.

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Cetin, Yucel. "Teaching Logarithm By Guided Discovery Learning And Real Life Applications." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12604957/index.pdf.

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The purpose of the study was to investigate the effects of discovery and application based instruction (DABI) on students&rsquo
mathematics achievement and also to explore opinions of students toward DABI. The research was conducted by 118 ninth grade students from Etimesgut Anatolian High School, in Ankara, during the spring semester of 2001-2002 academic year. During the study, experimental groups received DABI and control groups received Traditionally Based Instruction (TBI). The treatment was completed in three weeks. Mathematics Achievement Test (MAT) and Logarithm Achievement Test (LAT) were administered as pre and posttest respectively. In addition, a questionnaire, Students&rsquo
Views and Attitudes About DABI (SVA) and interviews were administered to determine students&rsquo
views and attitudes toward DABI. Analysis of Covariance (ANCOVA), independent sample t-test and descriptive statistics were used for testing the hypothesis of the study. No significant difference was found between LAT mean scores of students taught with DABI and traditionally based instruction when MAT test scores were controlled. In addition, neither students&rsquo
field of study nor gender was a significant factor for LAT scores. Students&rsquo
gender was not a significant factor for SVA scores. However, there was significant effect of math grades and field selections of students on SVA scores.
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Panduwawala, Tharindi. "Natural product guided antibacterial drug discovery : tetramates as core scaffolds." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:b507ca4d-ef35-4928-90a2-0a3f774a4ed2.

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This thesis describes the synthesis and biological evaluation of a library of compounds containing the tetramic acid core in search of novel antibacterial drug candidates. Chapter 1 discusses the need for new antibiotics due to the emergence of virulent bacterial strains resistant to clinically available drugs and the hiatus in the discovery of new replacement antibitoics that has become a global threat to human health. Different platforms for antibacterial drug discovery and the re-emergence of natural products-based approach that has gained importance in the quest for novel antibiotics are discussed. In this regard, the intrinsic antibacterial activity of natural products containing a tetramate core structure and the strategies developed to synthesise the core scaffold are described. Chapter 2 discusses the use of ʟ-serine and ʟ-cysteine in tetramic acid synthesis and the application of ʟ-cysteine-derived thiazolidine templates suitable for stereoselective ring closing reactions to obtain the tetramic acid core with scope for further functionalization. Chapters 3 and 4 describe a range of synthetic routes for appropriate substitutions of the tetramate core for compound library generation. Elaboration of the tetramate core via carboxamide tetramate synthesis, Suzuki-Miyaura cross-coupling reactions, glycosylations and their aglycone analogue synthesis, etherification, tetramate-pyroglutamate systems, Buchwald aminations/amidations, cycloadditions and β-lactam hybrids as possible chemical modifications of the tetramate core structure are discussed. Chapter 5 describes the antibacetiral activity and physicochemical properties of the library of compounds synthesised. A preliminary evaluation of their antibiotic activity was conducted against S. aureus and E. coli using the hole-plate method. MICs of the tetramates synthesised were determined against several Gram-negative strains; Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Gram-positive strains; MRSA, Enterococcus faecalis and Streptococcus pneumoniae, in whole-cell bioassays. Physicochemical properties of the compound library were analysed to map the chemical space occupied by tetramates with potent antibacterial activity. Enzyme inhibition studies were conducted to identify possible modes of action that contribute to whole-cell antibiotic activity and in this regard, the inhibition of enzymes S. aureus topoisomerase IV, S. aureus RNA polymerase, E. coli RNA polymerase, E. coli gyrase and M. tuberculosis gyrase are discussed. Since plasma protein binding of compounds is an important factor that determines the bioavailability of antibiotics and their clinical outcome, a study of the binding affinity of these drug candidates to Human Serum Albumin (HSA) by both whole-cell bioassay and NMR spectroscopy-based protein binding experiments are discussed. Finally, a brief note on the potential of tetramic acids to function as proteasome inhibitors in anticancer chemotherapy is included at the end of this chapter.
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Kellner, Franziska. "Genome and transcriptome guided gene discovery in plant secondary metabolism." Thesis, University of East Anglia, 2016. https://ueaeprints.uea.ac.uk/63112/.

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Plants produce a wide range of complex secondary metabolites that have many applications, for example as pharmaceutical agents. Gene discovery and the elucidation of these unique biosynthetic pathways is challenging since many of the enzymatic transformations are unprecedented. In Catharanthus roseus, the sole producer of the valuable anti-cancer compounds vinblastine and vincristine, the biosynthetic pathway for these alkaloids is highly complex and crucial steps are still unknown. Recently, the tight transcriptional co-regulation of the early part of this pathway enabled discovery of some of the central enzymatic steps by analysing the gene co-expression patterns and testing potential candidates using virus induced gene silencing. Additionally, it has become apparent that some plant secondary metabolite pathways exhibit physical clustering of pathway related genes in the genome. This thesis highlights how both strategies of gene discovery can be applied for the targeted discovery of genes for missing steps in biosynthesis of non-model plants. Co-expression analysis to identify candidates and subsequent testing of these candidates using virus induced gene silencing has led to the discovery and subsequent characterisation of the enzyme tabersonine 3-oxygenase (T3O), a key oxidation step in vindoline biosynthesis. This thesis furthermore reports the first C. roseus whole genome sequence. Additionally a BAC library was obtained and selected BACs sequenced. Analysis of the combined sequencing data established that gene clustering does indeed occur for alkaloid biosynthesis in C. roseus and yielded a new set of candidates for so far unknown pathway enzymes. Selected candidates have been tested by silencing or expression and results are discussed. The sequence information provides a valuable resource for the wider community, available as a searchable, publically available database (http://medicinalplantgenomics.msu.edu/). The work presented in this thesis highlights how next generation sequence data can be exploited to elucidate complex secondary metabolic pathways.
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Yang, Di. "Analysis guided visual exploration of multivariate data." Worcester, Mass. : Worcester Polytechnic Institute, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-050407-005925/.

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Isesund, Robert. "TGfU och Enhanced Guided Discovery i fotbollsträning : Observation av en akademitränares arbetssätt." Thesis, Gymnastik- och idrottshögskolan, GIH, Institutionen för idrotts- och hälsovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:gih:diva-3734.

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Sammanfattning Syfte och frågeställningar Syftet med studien är att utvärdera hur en fotbollstränare i en ungdomsakademi bedriver fotbollsträning utifrån de teoretiska ramverken Teaching Games for Understanding (TGfU) och Enhanced Guided Discovery (EGD) i syfte att skapa effektivisering i lärande samt starkare självbestämmande motivation. Detta leder till följande frågeställningar: * Hur stor del av träningar med syfte att utveckla spelförståelse, taktik och teknik ägnas åt övningar som är isolerade respektive funktionella? * Hur stor del av träningstiden ägnas åt paus/samling och effektiv träningstid? * Är tränarens arbetssätt präglat av EGD vid inlärning av spelförståelse och teknik? Metod I studien medverkar en tränare för ett akademilag i fotboll. Denne har observerats utifrån den svenska versionen av CAIS (Coaches Analysis Intervention System). CAIS har modifierats utifrån Stenling (2013). Observationerna är utförda i realtid och omfattar fem träningspass med akademitränaren. Akademitränaren var cirka 26 år och har genomgått utbildningen UEFA B, spelarna i laget akademitränaren ansvarade för var cirka 14 år gamla under studien. Resultat Tidfördelningen under träningarna var till playing forms fördel. Då denna träningsaktivitet, inklusive samlingar och pauser, upptog 81,2 % av träningstiden totalt. Effektiv träningstid upptar 65,5 % av träningstiden, effektiv tid i playing form upptar 49,9 %. Akademitränarens beteende präglades utöver, ”tystnad-fokus på träning” och ”organiserande”, av frågetekniker och positiv feedback, både generell och specifik. Detta medför att akademitränarens arbetssätt och metodik präglas av EGD. Slutsats Akademitränarens arbetssätt är influerat av teorierna TGfU och EGD. Genom detta arbetssätt kan tränaren, enligt teorierna, skapa förutsättningar för långsiktig utveckling samt spelarens förmåga att hantera pressade situationer. Dessutom ger det även ökad möjlighet att stärka den självbestämmande motivationen hos enskilda spelare enligt SDT. I ett verkligt perspektiv kan studien användas som exempel på hur TGfU och EGD används praktiskt.
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Books on the topic "Guided discovery"

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B, Sund Robert, ed. Guided discovery activities for elementary school science. 2nd ed. Columbus: Merrill Pub. Co., 1989.

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Carin, Arthur A. Guided discovery activities for elementary school science. 4th ed. Upper Saddle River, N.J: Merrill, 1997.

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Guided discovery activities for elementary school science. 3rd ed. New York: Merrill, 1993.

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Göbel, Lisa. Technology-Assisted Guided Discovery to Support Learning. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-32637-1.

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Becoming a praying person: A guided discovery for groups and individuals. Chicago, Ill: LoyolaPress, 2005.

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Perrotta, Kevin. Proverbs: Wisdom for living : a guided discovery for groups and individuals. Chicago: Loyola Press, 2003.

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Perrotta, Kevin. Jesus, man of prayer: A guided discovery for groups and individuals. Chicago, Ill: Loyola Press, 2007.

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Meditations for self-discovery: Guided journeys for communicating with your inner self. New York: Summerjoy Press, 1995.

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Living for a just society: A guided discovery for groups and individuals. Chicago, Ill: LoyolaPress., 2005.

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Psalms II: Praying with Jesus : a guided discovery for groups and individuals. Chicago: Loyola Press, 2003.

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Book chapters on the topic "Guided discovery"

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Neenan, Michael, and Windy Dryden. "Guided Discovery." In Cognitive Behaviour Therapy, 90–92. Third edition. | London; New York: Routledge, Taylor & Francis Group, 2021. | Series: 100 key points and techniques: Routledge, 2020. http://dx.doi.org/10.4324/9781003134053-38.

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Lavine, Robert A. "Guided Discovery Learning." In Encyclopedia of the Sciences of Learning, 1402–3. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_526.

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Ramma, Yashwantrao, Ajeevsing Bholoa, and Mike Watts. "Guided Discovery—Robert Gagné." In Springer Texts in Education, 191–208. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43620-9_14.

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McKenna, Elizabeth, and Barry Smyth. "Competence-Guided Case Discovery." In Research and Development in Intelligent Systems XVIII, 97–108. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0119-2_8.

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Azencott, Chloé-Agathe. "Network-Guided Biomarker Discovery." In Lecture Notes in Computer Science, 319–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50478-0_16.

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Seki, Kazuhiro, Yoshihiro Kino, and Kuniaki Uehara. "Gene Functional Annotation with Dynamic Hierarchical Classification Guided by Orthologs." In Discovery Science, 425–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04747-3_35.

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Burattin, Andrea. "User-Guided Discovery of Process Models." In Process Mining Techniques in Business Environments, 113–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17482-2_13.

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Schmid, Molly B. "Structure-Guided Discovery of New Antimicrobial Agents." In Antibiotic Discovery and Development, 969–84. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4614-1400-1_31.

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Burger, Klaus. "Pharmacogenomic-Guided Drug Development." In Drug Discovery and Evaluation: Methods in Clinical Pharmacology, 551–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-540-89891-7_39.

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Oikarinen, Emilia, Kai Puolamäki, Samaneh Khoshrou, and Mykola Pechenizkiy. "Supervised Human-Guided Data Exploration." In Machine Learning and Knowledge Discovery in Databases, 85–101. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43823-4_8.

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Conference papers on the topic "Guided discovery"

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Castell-Uroz, Ismael, Josep Sole-Pareta, and Pere Barlet-Ros. "TrackSign: Guided Web Tracking Discovery." In IEEE INFOCOM 2021 - IEEE Conference on Computer Communications. IEEE, 2021. http://dx.doi.org/10.1109/infocom42981.2021.9488842.

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Phillips, Joseph, and Bruce G. Buchanan. "Ontology-guided knowledge discovery in databases." In the international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/500737.500758.

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Gilpin, Sean, Tina Eliassi-Rad, and Ian Davidson. "Guided learning for role discovery (GLRD)." In KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2487575.2487620.

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Milne, R. "Knowledge guided data mining." In IEE Colloquium on Knowledge Discovery in Databases. IEE, 1995. http://dx.doi.org/10.1049/ic:19950117.

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Alonso, Rafael, and Hua Li. "Model-guided information discovery for intelligence analysis." In the 14th ACM international conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1099554.1099621.

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Maggi, Fabrizio M., Arjan J. Mooij, and Wil M. P. van der Aalst. "User-guided discovery of declarative process models." In 2011 Ieee Symposium On Computational Intelligence And Data Mining - Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/cidm.2011.5949297.

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Siddiqui, Md Amran, Alan Fern, Thomas G. Dietterich, Ryan Wright, Alec Theriault, and David W. Archer. "Feedback-Guided Anomaly Discovery via Online Optimization." In KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219819.3220083.

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Kypuros, Javier A., Constantine Tarawneh, Horacio Vasquez, Martin Knecht, and Robert Wrinkle. "Lessons learned implementing and optimizing Guided Discovery modules." In 2012 IEEE Frontiers in Education Conference (FIE). IEEE, 2012. http://dx.doi.org/10.1109/fie.2012.6462463.

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Guo, Jin L. C., Natawut Monaikul, and Jane Cleland-Huang. "Domain Knowledge Discovery Guided by Software Trace Links." In 2018 5th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE). IEEE, 2018. http://dx.doi.org/10.1109/aire.2018.00006.

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Yerizon, Meisa Kurnia, and Yerizon. "Learning Device Practicality Based on Guided Discovery Learning." In Proceedings of the 2nd International Conference on Mathematics and Mathematics Education 2018 (ICM2E 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icm2e-18.2018.44.

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Reports on the topic "Guided discovery"

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Garton, Byron, Jonathan Broderick, and Michael Clement. Discover Employees user’s guide. Engineer Research and Development Center (U.S.), September 2020. http://dx.doi.org/10.21079/11681/38228.

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Jarron, Matthew, Amy R. Cameron, and James Gemmill. Dundee Discoveries Past and Present. University of Dundee, November 2020. http://dx.doi.org/10.20933/100001182.

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A series of self-guided walking tours through pioneering scientific research in medicine, biology, forensics, nursing and dentistry from the past to the present. Dundee is now celebrated internationally for its pioneering work in medical sciences, in particular the University of Dundee’s ground-breaking research into cancer, diabetes, drug development and surgical techniques. But the city has many more amazing stories of innovation and discovery in medicine and biology, past and present, and the three walking tours presented here will introduce you to some of the most extraordinary. Basic information about each topic is presented on this map, but you will ­find more in-depth information, images and videos on the accompanying website at uod.ac.uk/DundeeDiscoveriesMap For younger explorers, we have also included a Scavenger Hunt – look out for the cancer cell symbols on the map and see if you can ­find the various features listed along the way!
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Garton, Byron, Jonathan Broderick, and Michael Clement. Discover ERDC Support Staff user’s guide. Engineer Research and Development Center (U.S.), September 2020. http://dx.doi.org/10.21079/11681/38231.

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Garton, Byron, Jonathan Broderick, and Michael Clement. Discover ERDC Knowledge Management Representative (KMR) user’s guide. Engineer Research and Development Center (U.S.), October 2020. http://dx.doi.org/10.21079/11681/38359.

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Mahat, Marian, and Wesley Imms. Archipelago of Possibilities: Facilitator Guide. University of Melbourne, 2020. http://dx.doi.org/10.46580/124323.

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Abstract:
Archipelago of Possibilities is a strategy and professional development workshop created specifically to help teachers and educators uncover what they hold dear in their teaching practice and discover what they consider most important for a successful practice. This workshop uses travel as a metaphor to guide participants in reflecting on their practice, identifying successful factors for success, examining what is holding them back from achieving their ideal practice, and developing steps to create a future ideal teaching and learning space.
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Grzybowski, Bartosz A. Engines of discovery: Computers in advanced synthesis planning and identification of drug candidates. AsiaChem Magazine, November 2020. http://dx.doi.org/10.51167/acm00010.

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After over five decades of efforts, computers have recently begun to plan chemical syntheses of complex targets at a level comparable to human experts. With this milestone achieved, it is now time to ponder not only how the machines will accelerate and multiplex synthetic design, but also how they will guide the discovery of new targets having desired properties.
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