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Academic literature on the topic 'Assignments'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 August 2024

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Journal articles on the topic "Assignments"

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K G, Binu, Yathish Kumar K, Rolvin D’Silva, Vinoothan Kaliveer, Ashwin Shetty, Glenson Toney, Sathyendra Bhat, Roopesh ., and Athokpam Bikramjit Singh. "Integrating Real-World Applications into the Machine Design Course through an Open-Ended Assignment – A Case Study." Journal of Engineering Education Transformations 37, IS2 (January 1, 2024): 879–86. http://dx.doi.org/10.16920/jeet/2024/v37is2/24135.

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This paper presents a case study in engineering education, focusing on enhancing conceptual understanding, realworld application, comprehension, teamwork, self-directed learning, and familiarity with design codes and standards. The study involves student analysis of artifact safety and optimization, engaging them in practical problem-solving. The outlined methodology covers artifact selection, analysis, and assessment of the assignment's impact. The findings exhibit improvements in knowledge acquisition, real-world relevance, teamwork, and selflearning. Moreover, the study highlights the assignment's enhanced appeal and challenge compared to conventional assignments. Students express a preference for more such assignments over routine ones. The paper underscores experiential learning's significance in cultivating critical skills for modern engineering and advocates integrating practical applications into curricula for holistic skill development. Keywords—Conceptual Understanding; Experiential Learning; Engineering Education; Real-World Applications; Open-Ended Assignments; Assignment Impact.
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Fitriani, Pipit Eka, Regina Aulia Uriemanda, Resty Widiastuti, Iwan Ridwan Yusup, and Milla Listiwati. "PERBANDINGAN PENUGASAN KELOMPOK DAN INDIVIDU TERHADAP HASIL BELAJAR PADA MATA KULIAH GENETIKA MAHASISWA PENDIDIKAN BIOLOGI SEMESTER 6B." Pedagonal : Jurnal Ilmiah Pendidikan 4, no. 1 (April 12, 2020): 21–25. http://dx.doi.org/10.33751/pedagonal.v4i1.1933.

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COMPARISON OF GROUP AND INDIVIDUAL ASSIGNMENTS ON LEARNING OUTCOMES IN GENETIC COURSES OF BIOLOGY EDUCATION COLLEGE STUDENTSTo create a dynamic form in academic field, assignments are given by the lecturer within the process of the study. These assignments are given both to individuals and groups with different purposes. This research is aim to see the impacts of giving group assignments and individual assignments to student’s learning outcomes. The research method used was pre-experimental design research. The research subjects were students of biology education in semester 6 of 2014/2015 academic year. The results of the analysis show the average value of the group assignment is lower at 79.33 compared to the average value of the individual assignment of 80.22. Inferential analysis showed a significant group assignment value of 0.00 ˂ 0.05. Thus, we can conclude that the results of group assignments are significant compared to the results of individual assignments..
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Fitriani, Pipit Eka, Regina Aulia Uriemanda, Resty Widiastuti, Iwan Ridwan Yusup, and Milla Listiwati. "PERBANDINGAN PENUGASAN KELOMPOK DAN INDIVIDU TERHADAP HASIL BELAJAR PADA MATA KULIAH GENETIKA MAHASISWA PENDIDIKAN BIOLOGI SEMESTER 6B." Pedagonal : Jurnal Ilmiah Pendidikan 4, no. 1 (March 29, 2020): 21–25. http://dx.doi.org/10.33751/pedagonal.v4i1.1989.

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COMPARISON OF GROUP AND INDIVIDUAL ASSIGNMENTS ON LEARNING OUTCOMES IN GENETIC COURSES OF BIOLOGY EDUCATION COLLEGE STUDENTSTo create a dynamic form in academic field, assignments are given by the lecturer within the process of the study. These assignments are given both to individuals and groups with different purposes. This research is aim to see the impacts of giving group assignments and individual assignments to student’s learning outcomes. The research method used was pre-experimental design research. The research subjects were students of biology education in semester 6 of 2014/2015 academic year. The results of the analysis show the average value of the group assignment is lower at 79.33 compared to the average value of the individual assignment of 80.22. Inferential analysis showed a significant group assignment value of 0.00 ˂ 0.05. Thus, we can conclude that the results of group assignments are significant compared to the results of individual assignments..
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LUBENCHENKO, О., and S. SHULHA. "Selection and Monitoring of Assignments in the Audit of Financial Reporting." Scientific Bulletin of the National Academy of Statistics, Accounting and Audit, no. 4 (November 3, 2021): 45–59. http://dx.doi.org/10.31767/nasoa.4-2020.06.

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Problems related to the quality assessment of completed audit assignments are analyzed. As the increasing number of users take management decisions on the basis of audit reports, independent audit is intended to guarantee a sound verification of financial reporting at company level, which can be achieved through the procedures for the assignment quality control. The article’s objective is to develop methodical recommendations on quality assessment of individual auditing assignments for auditing firms. An analytical review of the normative criteria for selection of assignments for monitoring is made, and the authors’ criteria based on the risk oriented approach to the assessment of assignments of the financial audit are proposed: (i) obligatory auditing, including the auditing of financial reporting of companies with public significance (50% of the total number of the assignments in obligatory audit); (ii) voluntary audit (at least one assignment of the key partner), with the review of financial reporting covering 10% of the total number of the review assignments; other assignments covering 10% or more of the total number of the assignments on providing reassurance, which is not audit or review; selection of the most risky assignments with high level of the implicit risk; related services covering 10% of the total number of assignments pertaining to related services on agreed procedures and compilation of information (with selecting most complicated issues of business operation, which were subject to concern in providing related services and assignments for a new customer). A four-phase model of the assessment of selected assignments of an auditing firm is elaborated: acceptance of customer and assignment; planning and assessment of risks; assignment completion; formulation of auditor opinion and control actions on quality assurance. The practical implementation of this model involves documenting of the internal control of the quality of audit, analysis of results of the quality control, accumulation of errors and correcting actions at system and assignment level.
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Neller, Todd W., Stephen Keeley, Michael Guerzhoy, Wolfgang Hoenig, Jiaoyang Li, Sven Koenig, Ameet Soni, et al. "Model AI Assignments 2020." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 09 (April 3, 2020): 13509–11. http://dx.doi.org/10.1609/aaai.v34i09.7072.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of nine AI assignments from the 2020 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.
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Neller, Todd W., Raja Sooriamurthi, Michael Guerzhoy, Lisa Zhang, Paul Talaga, Christopher Archibald, Adam Summerville, et al. "Model AI Assignments 2019." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9751–53. http://dx.doi.org/10.1609/aaai.v33i01.33019751.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of ten AI assignments from the 2019 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http: //modelai.gettysburg.edu.
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Neller, Todd W., Nathan Sprague, John Maraist, Lisa Zhang, Pouria Fewzee, Duri Long, Jonathan Moon, et al. "Model AI Assignments 2021." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 17 (May 18, 2021): 15705–6. http://dx.doi.org/10.1609/aaai.v35i17.17850.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of six AI assignments from the 2021 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.
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Neller, Todd W., Jazmin Collins, Daniel Schneider, Yim Register, Christopher Brooks, Chiawei Tang, Chaolin Liu, et al. "Model AI Assignments 2022." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (June 28, 2022): 12863–64. http://dx.doi.org/10.1609/aaai.v36i11.21569.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of six AI assignments from the 2022 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.
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Neller, Todd W., Raechel Walker, Olivia Dias, Zeynep Yalçın, Cynthia Breazeal, Matt Taylor, Michele Donini, et al. "Model AI Assignments 2023." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 13 (June 26, 2023): 16104–5. http://dx.doi.org/10.1609/aaai.v37i13.26913.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of six AI assignments from the 2023 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu .
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Neller, Todd, Laura Brown, John Earnest, Jason Hiebel, and Douglas Turnbul. "Model AI Assignments 2012." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 3 (October 4, 2021): 2377–78. http://dx.doi.org/10.1609/aaai.v26i3.18957.

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The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning ex- perience, we here present abstracts of three AI assignments from the 2012 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.
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Dissertations / Theses on the topic "Assignments"

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Young, Katherine McCreight. "Multiple case assignments." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/14409.

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Benders, Tori. "Service Learning Assignments: The Interesect Between Assignment Framing, Student Motivation, and Perceived Relevance." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28855.

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Although learning has traditionally happened within the four walls of a classroom, as service learning courses become more prevalent, instructors are challenging their students to take learning outside of the classroom and into the community. Service learning has the potential to transform students and their learning, it is not widely known how to ensure students are motivated to complete these assignments and see them as relevant to their futures. This study used social determination theory and a 2X2 experimental design to survey 271 students about their motivation to complete a service learning project presented to them in an assignment sheet and perceived relevance of the assignment and overall attitude toward service learning. Findings indicate that overall students have positive attitudes toward service learning, are moderately motivated to complete service learning assignments, and see them as relevant. How the assignment sheet is framed largely does not have implications for these feelings.
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Patching, Robert Steven. "Truth-space mass assignments." Thesis, Loughborough University, 2005. https://dspace.lboro.ac.uk/2134/34119.

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The theory of mass assignments allows reasoning using probability families that are either imprecise, incomplete or both. The majority of previous work has been with mass assignments defined upon arbitrary domains. This Thesis concentrates on a neglected specialisation of mass assignments, the truth-space mass assignments defined upon the power set of Booleans. The semantics of truth-space mass assignments and their operators are described, both in relation to general mass assignments and also with other methods of imprecise and incomplete reasoning. New operators are defined for truth-space mass assignments that allow them to be reasoned with in new ways consistent with other logic systems. Alterations are made to existing operators to allow them to act in a more intuitive way. Using the new and altered operators this Thesis allows mass assignment theory to act as a many-valued logic handling imprecise and incomplete truths. This opens up many new topics of research and potential for applying the method to solve problems in a new way.
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Govett, A., Bill J. Garris, Renee Rice Moran, Ryan A. Nivens, and Alison L. Barton. "Summer Research Assignments Report." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/4737.

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Hamendi, Mohammed. "Automatically Testing Student Assignments." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-202110.

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The freshmen programming courses at the University of Economics in Prague offer a unique approach to learning the art of programming and software engineering. The introductory courses follow the Architecture First methodology that gives students the opportunity to learn programming from the top down, without being constrained by the specifics and syntax of any one programming language. It teaches the thought processes needed to build programs, allowing the student to absorb the big ideas of computer programming. The average number of freshmen at the faculty of Informatics and Statistics is around seven hundred students. The task of correcting programming assignment and preparing appropriate feedback would be a mammoth undertaking for teaching staff in most university settings worldwide that offer similar computing degrees. It is therefore quite often the case that the faculty provisions some sort of automated testing technology that can handle the volume and provide both the teaching staff and the students with the tools needed to manage the assignments. These automated tools or systems have been, and continue to be, the subject of many research topics across the world and continue to evolve as new technologies and teaching methods evolve. This study first introduces the theoretical background of automated assessment and grading tools and systems and then provides an analysis of the fields current state. Taking that as input to the next phase, the study uses that information to then design and implement a custom-built system that would enable the automated testing of the structure and other aspects of student assignments. The main goal for the resulting system is to provide an intuitive and convenient way of declaring what needs to be tested for a given assignment and then providing the mechanism to run those tests automatically. The resulting system, DynoGrader, dynamically validates student assignments at runtime using Java runtime annotation processing mechanisms and Java Reflection API.
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Williams, Delize. "Paperless assignments : a closer look." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33040.

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With the increasing student population at many tertiary level institutions, the management of assignment submissions and results has become a challenging feat. This thesis proposes that one way to address these challenges is to develop methods for automating the submission of assignments to support the administrative effort. This will not only enable many administrative tasks to be automated, but will also support and in some cases, improve the learning experience available to students.
The features of four paperless assignment submission systems are presented, compared and analyzed with the goal of exposing instructors to the varied benefits that such systems can provide, thereby encouraging them to use such systems in their course delivery.
It is also the intent that this thesis will form the basis from which further developmental work will be performed on such systems in general, and on VisualCM in particular. (VisualCM is a paperless assignment submission system currently used within the School of Computer Science at McGill University).
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Enoka, Maro D. "Optimizing Marine Security Guard assignments." Thesis, Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/5637.

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Approved for public release; distribution is unlimited.
The Marine Corps Embassy Security Group (MCESG) assigns 1,500 Marine Security Guards (MSGs) to 149 embassy detachments annually. While attempting to fulfill several billet requirements, MCESG strives to balance MSG experience levels at each embassy detachment and assign MSGs to their preferred posts. The current assignment process is accomplished manually by three Marines and takes more than 6,000 hours per year. This thesis presents the Marine Security Guard Assignment Tool (MSGAT). MSGAT is an Excel-based decision support tool that utilizes a system of workbooks to guide MCESG through a streamlined data collection and provide optimal assignments. MSGAT assignments result in a higher satisfaction when compared with manual assignments. MSGAT has had an immediate and quantifiable impact on the assignment process. It has reduced person-hours by 80%, increased overall assignment quality and efficiency and improved the operational readiness of MCESG by optimizing MSG assignments.
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Beaulieu, Marie-Claire, and Tim Buckingham. "Classroom epigraphy assignments with Perseids." Epigraphy Edit-a-thon : editing chronological and geographic data in ancient inscriptions ; April 20-22, 2016 / edited by Monica Berti. Leipzig, 2016. Beitrag 3, 2016. https://ul.qucosa.de/id/qucosa%3A15466.

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Viyyure, Uday Kiran Varma. "Frequency Assignments in Radio Networks." Kent State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=kent1209060158.

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Beaulieu, Marie-Claire, and Tim Buckingham. "Classroom epigraphy assignments with Perseids." Universitätsbibliothek Leipzig, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-221500.

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Books on the topic "Assignments"

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Nicholls, Jeff. Design assignments. Nepean, ON: Bacon & Hughes Limited, 1997.

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Cole, Maureen. Keyboarding Assignments. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-11392-7.

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Tibbertsma, A. Science assignments. Melbourne: Macmillan, 1989.

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Morgan, Cheryl. Writing assignments. London: Learning and Skills Development Agency, 2001.

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Akunin, B. Special assignments. New York: Random House Trade Paperbacks, 2008.

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Lenehan, Brian A. English assignments. Dublin: Educational Company, 1994.

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Beashel, Paul. Sport assignments. Basingstoke: Macmillan Education, 1988.

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Lenehan, Brian A. English Assignments. Dublin: The Educational Company, 1995.

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Keene, Carolyn. International Assignments. London: Simon & Schuster ltd, 1993.

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Delaygua, Joaquín J. Forner. La cesión de contrato: Construcción de la figura y ley aplicable. Barcelona: Bosch, 1989.

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Book chapters on the topic "Assignments"

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Penketh, F. E. "Assignments." In Work Out Numeracy, 227–49. London: Macmillan Education UK, 1987. http://dx.doi.org/10.1007/978-1-349-08605-4_15.

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Gehrke, Wilhelm. "Assignments." In Fortran 95 Language Guide, 105–26. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-1025-5_8.

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Sallis, Edward, and Kate Sallis. "Assignments." In People in Organisations, 245–56. London: Macmillan Education UK, 1988. http://dx.doi.org/10.1007/978-1-349-09228-4_26.

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Gil-Aluja, Jaime. "Assignments." In Applied Optimization, 125–81. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-3011-1_3.

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Penketh, Ted. "Assignments." In Work Out Numeracy, 225–38. London: Macmillan Education UK, 1996. http://dx.doi.org/10.1007/978-1-349-14099-2_16.

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Groucutt, Jonathan. "Assignments." In Business Degree Success, 104–30. London: Macmillan Education UK, 2008. http://dx.doi.org/10.1007/978-1-137-06149-2_9.

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Mukherjee, Chinmoy. "Assignments." In Build Android-Based Smart Applications, 117–25. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3327-6_11.

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Klein Haneveld, Willem K., Maarten H. van der Vlerk, and Ward Romeijnders. "Assignments." In Stochastic Programming, 163–79. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29219-5_7.

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Gehrke, Wilhelm. "Assignments." In Fortran 90 Language Guide, 101–14. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3014-7_8.

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Alencar, Marcelo Sampaio de, and Thiago Tavares de Alencar. "Assignments." In Scientific Style in English, 125–26. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003339366-9.

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Conference papers on the topic "Assignments"

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Kimura, Kei, and Kazuhisa Makino. "Linear Satisfiability Preserving Assignments (Extended Abstract)." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/797.

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In this paper, we study several classes of satisfiability preserving assignments to the constraint satisfaction problem. In particular, we consider fixable, autark and satisfying assignments. Since it is in general NP-hard to find a nontrivial (i.e., nonempty) satisfiability preserving assignment, we introduce linear satisfiability preserving assignments, which are defined by polyhedral cones in an associated vector space. The vector space is obtained by the identification, introduced by Kullmann, of assignments with real vectors. We consider arbitrary polyhedral cones, where only restricted classes of cones for autark assignments are considered in the literature. We reveal that cones in certain classes are maximal as a convex subset of the set of the associated vectors, which can be regarded as extensions of Kullmann's results for autark assignments of CNFs. As algorithmic results, we present a pseudo-polynomial time algorithm that computes a linear fixable assignment for a given integer linear system, which implies the well known pseudo-polynomial solvability for integer linear systems such as two-variable-per-inequality, Horn and q-Horn systems.
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Yadin, Aharon. "INDIVIDUALIZED ASSIGNMENTS FOR IMPOSING BETTER LEARNING HABITS IN THE "SHARE EVERYTHING" GENERATION." In eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-140.

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This paper describes a follow-on study related to the effects of personal and individual assignments on the students' learning habits. The current students' generation (Generation Y) is sometimes defined as "friends with everybody and share everything". This phenomenon, when applied to learning has a negative impact as was demonstrated by a large difference between the assignments grades and the exam grades. A possible explanation is that the assignments' grades do not provide a real representation of the students' knowledge. In trying to address this issue, a method of personal and individual assignments was used as part of a Software Project's Management course. By using this method each student receives a different assignment, so sharing the results is impossible. Furthermore, each assignment has two stages. The first is the assignment itself, and in the second the student has to assess an assignment submitted by another student. This dual stage learning has reduced the large gap between the assignments' grades and the exam grades. As part of the study, one of the assignments was a "standard" assignment in which all students received the same one. In this case, the average grade was very high and the abovementioned gap reappeared. Most of the modern research into effective learning is aimed at collaborative experiences in which the responsibility is transferred from the teacher to the student. Using personal and individual assignments enhances the students' accountability and does not undermine the collaboration importance. The paper describes the study and the results and concludes with a short discussion. The assumption that students who have a high degree of responsibility towards their learning will be better collaborators and will contribute to the team they are part of will be addressed in a follow-on study.
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Whittington, Keith. "Progressive Programminq Assignments." In InSITE 2005: Informing Science + IT Education Conference. Informing Science Institute, 2005. http://dx.doi.org/10.28945/2887.

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Progressive programming assignments were used in an introductory Java programming course where every assignment built on the previous one. The major goal was to help students learn difficult, abstract concepts. This technique allows students to concentrate on the current topic while building on their previous work. This also provides an incentive for students to keep up with their work. Students often feel that they can skip the current topic and pick up after it is over, but it is difficult to do this in a programming course because every new concept builds on the previous ones. This approach also has built-in scalability, which is difficult to achieve in introductory programming courses due to time constraints and the students limited knowledge. These assignments were given in a CS2-type course where the topics predominantly deal with abstract concepts. This paper discusses the assignments, goals, faculty observations, student comments, and results.
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Yadin, Aharon. "SHARING STUDENTS' RELATIVE PERFORMANCE FOR REINFORCING MOTIVATION." In eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-139.

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This paper describes an experimental study that was performed among undergraduate students in their third year out of four required for their Software Engineering degree. The study's main purpose that stems from Maslow's motivational theory (self-actualization) was to explore possible motivational increase through self-grades comparisons. For that reason, a small Excel tool was provided with relative performance comparison graphs. Each student could enter his or her ID number and receive a two graphs figure. One graph represents the average class grades for all assignments and the second graph represents his or her assignments' grades. All assignments were individualized and personalized, so every student got a different set of assignments. In addition to the personal feedback, every student received for each assignment the tool provided a self-comparative assessment. Using this assessment, each student could judge his or her relative performance as compared to the class average. As part of the study, a 56 Methods in Software Engineering students were divided into two groups. Students in one group (the test group) were able to access the Excel tool while the students in the second group (the control group), did not. The study revealed that the grades of the four assignments in the test group gradually increased while on the control group the average grades remained very close. For the first assignment, the control group's average grade was higher by one point compared to the test group. In the second assignment, the trend reversed, and the test group's average grade was higher by two points. The difference between the groups increased further, and in the fourth assignments the average grade of the test group was higher by 7 points compared to the control group. Furthermore, while the course average grade of the control group was similar to the grades in previous years, the course average grade in the test group was higher by 2 points. Students' reflection supported these findings as some students expressed their views regarding the importance of their relative performance. The paper concludes with a discussion on the results and future follow-up directions.
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Milanovic, Ivana, Tom A. Eppes, and Kalyan Goparaju. "Digital Assignments for Thermo-Fluids Courses." In ASME 2021 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/fedsm2021-65613.

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Abstract Simulations were used in lecture-based courses, Thermodynamics I and Thermodynamics II, for demonstration purposes and as digital assignments. Digital assignments were separate from the customary pencil & paper homework given once a week. The primary objective was to model the flow and heat transfer in a system, reinforce theoretical concepts, and allow study of more complex two- and three-dimensional problems. Students encounter fluid flow and heat transfer in the sophomore course, Thermodynamics I, for the first time. Velocity, pressure and temperature fields are quite complicated even for simple geometries, hard to visualize, and difficult to understand. Digital assignments go beyond basic theoretical concepts and relatively simple pencil & paper problems. Initially, there were 6 digital assignments in each course. After the first offerings and assessments, the number of assignments is expected to grow to 8–10. Scaffolding of digital assignments ensured that simulations gain in complexity as students become more familiar with both the theoretical underpinnings and the software interface. Our Mechanical Engineering program, has a freshmen graphic communication course incorporating AutoCAD and a junior CAD course with SolidWorks and Ansys. This provided both a challenge and an opportunity for lecture-based thermo-fluids courses positioned ‘in between.’ Modern computational skills were obtained outside the classroom, and that was accomplished with effective use of an on-line environment. Ansys Fluent was chosen to present and reinforce thermo-fluids fundamentals. Each digital assignment had a mesh, detailed grading criteria, and supplementary documentation. Students worked on the: (1) problem set up in the preprocessor-stage, (2) solver, and (3) postprocessor. This approach helped students (1) understand the flow and heat transfer inside the system as well as the application of conservation of mass and energy, (2) understand and interpret results by comparing them with theoretical and experimental data, (3) develop modern technical skills relevant to the demands of Industry 4.0, and (4) develop research capabilities. Simulations in the classroom and as digital assignments are a representation of the real world, and provide an egalitarian and unrestricted way for students to interact with it, acquiring skills and an appreciation for subject matter as well as the engineering profession. Semester long discussions on various aspects of digital assignments help develop a mentor-mentee bond. This approach to teaching, research and mentoring does not depend on access to laboratory facilities and funding that can reach only a limited number of students. It encourages students’ spirit of inquiry, and ultimately leads to a professional development opportunities beyond the classroom setting.
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Parlante, Nick, Jeffrey Popyack, Stuart Reges, Stephen Weiss, Scott Dexter, Chaya Gurwitz, Joseph Zachary, and Grant Braught. "Nifty assignments." In the 34th SIGCSE technical symposium. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/611892.611914.

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Parlante, Nick, Thomas P. Murtagh, Mehran Sahami, Owen Astrachan, David Reed, Christopher A. Stone, Brent Heeringa, and Karen Reid. "Nifty assignments." In the 40th ACM technical symposium. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1508865.1509031.

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Parlante, Nick, Julie Zelenski, Josh Hug, John Nicholson, John DeNero, Antti Laaksonen, Arto Vihavainen, Frank McCown, and Kevin Wayne. "Nifty assignments." In the 45th ACM technical symposium. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2538862.2538995.

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Parlante, Nick, Julie Zelenski, Keith Schwarz, Dave Feinberg, Michelle Craig, Stuart Hansen, Michael Scott, and David J. Malan. "Nifty assignments." In the 42nd ACM technical symposium. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1953163.1953305.

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Parlante, Nick, Julie Zelenski, Michelle Craig, John DeNero, Mark Guzdial, David J. Malan, Aditi Muralidharan, Eric Roberts, and Kevin Wayne. "Nifty assignments." In Proceeding of the 44th ACM technical symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2445196.2445356.

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Reports on the topic "Assignments"

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DEPARTMENT OF THE ARMY WASHINGTON DC. Assignments, Details, and Transfers: Enlisted Assignments and Utilization Management. Fort Belvoir, VA: Defense Technical Information Center, July 2001. http://dx.doi.org/10.21236/ada402434.

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Hinden, R., and S. Deering. IPv6 Multicast Address Assignments. RFC Editor, July 1998. http://dx.doi.org/10.17487/rfc2375.

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Meyer, D. Extended Assignments in 233/8. RFC Editor, June 2001. http://dx.doi.org/10.17487/rfc3138.

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DEPARTMENT OF THE ARMY WASHINGTON DC. Assignments, Details, and Transfers: Overseas Service. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada402432.

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Hinden, R., S. Deering, R. Fink, and T. Hain. Initial IPv6 Sub-TLA ID Assignments. RFC Editor, September 2000. http://dx.doi.org/10.17487/rfc2928.

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Wright, J., Steven Egly, and H. Gallivan. Systematic Analysis of Noninferior Transfer Assignments. West Lafayette, IN: Purdue University, 1985. http://dx.doi.org/10.5703/1288284314093.

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CORPS OF ENGINEERS WASHINGTON DC. Plant: Radio Frequency and Call Sign Assignments. Fort Belvoir, VA: Defense Technical Information Center, September 1986. http://dx.doi.org/10.21236/ada404085.

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Albanna, Z., K. Almeroth, D. Meyer, and M. Schipper. IANA Guidelines for IPv4 Multicast Address Assignments. RFC Editor, August 2001. http://dx.doi.org/10.17487/rfc3171.

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Cotton, M., L. Vegoda, and D. Meyer. IANA Guidelines for IPv4 Multicast Address Assignments. RFC Editor, March 2010. http://dx.doi.org/10.17487/rfc5771.

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Gray, E., J. Rutemiller, and G. Swallow. Internet Code Point (ICP) Assignments for NSAP Addresses. RFC Editor, May 2006. http://dx.doi.org/10.17487/rfc4548.

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