PurposeIn order to better understand how heuristics are used in practice, the authors explore what type of heuristics is used in the managerial domain of financial advisors to small and medium-sized enterprises (SMEs) and what influences the shaping of these heuristics. In doing so, the authors detect possible fast-and-frugal heuristics in day-to-day decision-making of independent financial advisers who help owners of SMEs to acquire capital (e.g. loans, factoring, leasing and equity).Design/methodology/approachThe authors inductively assessed the work of financial advisers of SMEs. Based on group discussions, the authors drew up a semi-structured interview-protocol with descriptive questions about how financial advisers come to a deal for their clients. The interviews of 19 professionals were analysed by relating them to the theory of fast-and-frugal heuristics.FindingsWithin their decision-making, advisers estimate the likelihood of acceptance by a few financial providers they know well in their personal network with a strong bias towards traditional banking products, although there are a large number of alternatives on the Dutch market. “Less is more” seems to be a relevant principle when defined as satisficing. Heuristics help advisers to deal with behavioural and economic limitations. Also, the authors have found that client interaction, previous working experience and the company the adviser is working for influences the shaping of the simple rules the adviser is using.Research limitations/implicationsThe study shows how difficult it is to understand the ecological rationality of a certain group of professionals and to understand the “less is more” principle. Financial advisers to SMEs use cognitive shortcuts and simple rules to advise SME-owners, based on previous experiences, but it is difficult to determine whether that leads to the same or even better solutions for them and their clients than using probability theory and financial optimisation models. Within heuristics, satisficing seems to be a dominant mechanism. Here, heuristics help advisers in recognising possibilities by searching for similarities between a current financing case and previous experiences. The data suggests that if “less is more” is defined as satisficing for one or more stakeholders involved, the principle dominates the decision making of financial advisers of SME's.Practical implicationsThe authors suggest the relevance of a behavioural approach to finance by assessing the day-to-day decisions of financial advisers of SMEs. Also, the authors suggest that financial advisers are guided by previous experiences, and they do not fully assess a wide range of options in their work but need shortcuts to fulfil the needs of their clients.Originality/valueThe study comes close to day-to-day decision-making in finance by assessing how professionals make decisions. The authors try to understand types of heuristics in relation with “ecological rationality” and the less is more principle. The authors assess financial advisers of SME-companies, a group that has gotten little research attention until now. The influence of client interaction and of the company the adviser is working for is remarkable in the shaping of the advisers' simple rules.
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Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.
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Active learning has become an increasingly popular method for screening large amounts of data in systematic reviews and meta-analyses. The active learning process continually improves its predictions on the remaining unlabeled records, with the goal of identifying all relevant records as early as possible. However, determining the optimal point at which to stop the active learning process is a challenge. The cost of additional labeling of records by the reviewer must be balanced against the cost of erroneous exclusions. This paper introduces the SAFE procedure, a practical and conservative set of stopping heuristics that offers a clear guideline for determining when to end the active learning process in screening software like ASReview. The eclectic mix of stopping heuristics helps to minimize the risk of missing relevant papers in the screening process. The proposed stopping heuristic balances the costs of continued screening with the risk of missing relevant records, providing a practical solution for reviewers to make informed decisions on when to stop screening. Although active learning can significantly enhance the quality and efficiency of screening, this method may be more applicable to certain types of datasets and problems. Ultimately, the decision to stop the active learning process depends on careful consideration of the trade-off between the costs of additional record labeling against the potential errors of the current model for the specific dataset and context.
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A primary teacher needs mathematical problem solving ability. That is why Dutch student teachers have to show this ability in a nationwide mathematics test that contains many non-routine problems. Most student teachers prepare for this test by working on their own solving test-like problems. To what extent does these individual problem solving activities really contribute to their mathematical problem solving ability? Developing mathematical problem solving ability requires reflective mathematical behaviour. Student teachers need to mathematize and generalize problems and problem approaches, and evaluate heuristics and problem solving processes. This demands self-confidence, motivation, cognition and metacognition. To what extent do student teachers show reflective behaviour during mathematical self-study and how can we explain their study behaviour? In this study 97 student teachers from seven different teacher education institutes worked on ten non-routine problems. They were motivated because the test-like problems gave them an impression of the test and enabled them to investigate whether they were already prepared well enough. This study also shows that student teachers preparing for the test were not focused on developing their mathematical problem solving ability. They did not know that this was the goal to strive for and how to aim for it. They lacked self-confidence and knowledge to mathematize problems and problem approaches, and to evaluate the problem solving process. These results indicate that student teachers do hardly develop their mathematical problem solving ability in self-study situations. This leaves a question for future research: What do student teachers need to improve their mathematical self-study behaviour? EAPRIL Proceedings, November 29 – December 1, 2017, Hämeenlinna, Finland
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Blended learning, a teaching format in which face-to-face and online learning is integrated, nowadays is an important development in education. Little is known, however, about its affordances for teacher education, and for domain specific didactical courses in particular. To investigate this topic, we carried out a design research project in which teacher educators engaged in a co-design process of developing and field-testing open online learning units for mathematics and science didactics. The preliminary results concern descriptions of the work processes by the design teams, of design heuristics, and of typical ways of collaborating. These findings are illustrated for the case of two of the designed online units on statistics didactics and mathematical thinking, respectively.
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The aim of this paper is to examine valuer judgement behaviour, by exploring the manifestation of task complexity in Dutch commercial valuation practice. For this purpose, we adopted a grounded theory approach and undertook 18 in-depth interviews with senior valuation professionals across the Netherlands. Our findings indicate a strong presence of situational task complexity in commercial valuation practice, as professionals operating in large valuation teams perceive different elements of task complexity throughout commercial valuation practice in comparison to peers working in small valuation teams or self-employed valuers. Further, coping strategies used to deal with task complexity vary substantially by type of valuer as well. From our data, we deducted three types of task environment constructs in which valuers operate, which basically represent the various levels of professional standards required by clients as well as organisational settings composed to meet client standards. As such, we found that task environment settings strongly coincide with perceptions of task complexity. The presence of situational task complexity in commercial real estate valuation practice points to the need for customisation of professional valuer’s development programs to facilitate valuers to deal with task complexity in different stages of valuation practice and hence contribute to advancing valuer judgement skills.
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In deze animatie bespreken we punten waar je als docent op moet letten als je samenwerkend leren wilt inzetten, waarbij je aan de hand van zeven stappen ondersteund wordt bij te maken keuzes.
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Sinds de invoering in 2002 van de bachelor-master structuur in het Nederlandse hoger onderwijs hebben Nederlandse instellingen voor hoger beroepsonderwijs hun bacheloropleidingen veelal opgedeeld in een major- en een minorgedeelte. De major vormt de hoofdmoot van de bacheloropleiding en wordt door alle studenten van de betreffende opleiding gevolgd. Minors zijn kleinere onderdelen van een bacheloropleiding, waarbij de student een keuze maakt uit een beschikbaar aanbod van minors. Minors bieden studenten de mogelijkheid hun bacheloropleiding vorm te geven op een wijze die aansluit bij hun persoonlijke ambities, interesses en kwaliteiten. Van hogescholen mag worden verwacht dat ze een passend minoraanbod ontwikkelen en dat ze studenten voorlichten over en begeleiden bij hun minorkeuze. Daarbij is het van belang kennis te hebben van beïnvloedingsfactoren van minorkeuze. Uit vooronderzoek blijkt dat nauwelijks iets bekend is waardoor studenten zich bij het maken van een minorkeuze laten beïnvloeden. Dit promotie-onderzoek beoogt een bijdrage te leveren aan het opvullen van deze leemte. Op basis van literatuuronderzoek en veldonderzoeken onder studenten van een zestal hogescholen die deel uitmaken van Fontys Hogescholen is in kaart gebracht door welke factoren studenten zich laten beïnvloeden bij het maken van een minorkeuze.
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Energy conservation is crucial in wireless ad hoc sensor network design to increase network lifetime. Since communication consumes a major part of the energy used by a sensor node, efficient communication is important. Topology control aims at achieving more efficient communication by dropping links and reducing interference among simultaneous transmissions by adjusting the nodes’ transmission power. Since dropping links make a network more susceptible to node failure, a fundamental problem in wireless sensor networks is to find a communication graph with minimum interference and minimum power assignment aiming at an induced topology that can satisfy fault-tolerant properties. In this paper, we examine and propose linear integer programming formulations and a hybrid meta-heuristic GRASP/VNS (Greedy Randomized Adaptive Search Procedure/Variable Neighborhood Search) to determine the transmission power of each node while maintaining a fault-tolerant network and simultaneously minimize the interference and the total power consumption. Optimal biconnected topologies for moderately sized networks with minimum interference and minimum power are obtained using a commercial solver. We report computational simulations comparing the integer programming formulations and the GRASP/VNS, and evaluate the effectiveness of three meta-heuristics in terms of the tradeoffs between computation time and solution quality. We show that the proposed meta-heuristics are able to find good solutions for sensor networks with up to 400 nodes and that the GRASP/VNS was able to systematically find the best lower bounds and optimal solutions.
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This paper discusses two studies - the one in a business context, the other in a university context - carried out with expert educational designers. The studies aimed to determine the priorities experts claim to employ when designing competence-based learning environments. Designers in both contexts agree almost completely on principles they feel are important. Both groups emphasized that one should start a design enterprise from the needs of the learners, instead of the content structure of the learning domain. However, unlike business designers, university designers find it extremely important to consider alternative solutions during the whole design process. University designers also say that they focus more on project plan and desired characteristics of the instructional blueprint whereas business designers report being more client-oriented, stressing the importance of "buying in" the client early in the process.
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