Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency

Kirschner, F., Paas, F., & Kirschner, P. (2009). Individual and group-based learning from complex cognitive tasks: Effects on retention and transfer efficiency. Computers in Human Behavior, 25, 306-314.The effects of individual versus group learning (in triads) on efficiency of retention and transfer test performance in the domain of biology (heredity) among 70 high-school students were investigated. Applying cognitive load theory, the limitations of the working memory capacity at the individual level were considered an important reason to assign complex learning tasks to groups rather than to individuals. It was hypothesized that groups will have more processing capacity available for relating the information elements to each other and by doing so for constructing higher quality cognitive schemata than individuals if the high cognitive load imposed by complex learning tasks could be shared among group members. In contrast, it was expected that individuals who learn from carrying out the same complex tasks would need all available processing capacity for remembering the interrelated information elements, and, consequently, would not be able to allocate resources to working with them. This interaction hypothesis was confirmed by the data on efficiency of retention and transfer test performance; there was a favorable relationship between mental effort and retention test performance for the individual learners as opposed to a favorable relationship between transfer test performance and mental effort for the students who learned in groups

Analysis of material efficiency aspects of personal computers product group

This report has been developed within the project ‘Technical support for environmental footprinting, material efficiency in product policy and the European Platform on Life Cycle Assessment’ (LCA) (2013-2017) funded by the Directorate-General for Environment. The report summarises the findings of the analysis of material-efficiency aspects of the personal-computer (PC) product group, namely durability, reusability, reparability and recyclability. It also aims to identify material-efficiency aspects which can be relevant for the current revision of the Ecodesign Regulation (EU) No 617/2013. Special focus was given to the content of EU critical raw materials (CRMs) ( ) in computers and computer components, and how to increase the efficient use of these materials, including material savings thanks to reuse and repair and recovery of the products at end of life. The analysis has been based mainly on the REAPro method ( ) developed by the Joint Research Centre for the material-efficiency assessment of products. This work has been carried out in the period June 2016-September 2017, in parallel with the development of The preparatory study on the review of Regulation 617/2013 (Lot 3) — computers and computer servers led by Viegand Maagøe and Vlaamse Instelling voor Technologisch Onderzoek NV (VITO) (2017) ( ). During this period, close communication was maintained with the authors of the preparatory study. This allowed ensuring consistency between input data and assumptions of the two studies. Moreover, outcomes of the present research were used as scientific basis for the preparatory study for the analysis of material-efficiency aspects for computers. The research has been differentiated as far as possible for different types of computers (i.e. tablet, notebooks and desktop computers). The report starts with the analysis of the technical and scientific background relevant for material-efficiency aspects of computers, such as market sales, expected lifetime, bill of materials, and a focus on the content of CRMs (especially cobalt in batteries, rare earths including neodymium in hard disk drives and palladium in printed circuit boards). Successively the report analyses the current practices for repair, reuse and recycling of computers. Based on results available from the literature, material efficiency of the product group has the potential to be improved, in particular the lifetime extension. The residence time ( ) of IT equipment put on the market in 2000 versus 2010 generally declined by approximately 10 % (Huisman et al., 2012), while consumers expressed their preference for durable goods, lasting considerably longer than they are typically used (Wieser and Tröger, 2016). Design barriers (such as difficulties for the disassembly of certain components or for their processing for data sanitisation) can hinder the repair and the reuse of products. Malfunction and accident rates are not negligible (IDC, 2016, 2010; SquareTrade, 2009) and difficulties in repair may bring damaged products to be discarded even if still functioning. Once a computer reaches the end of its useful life, it is addressed to ‘waste of electrical and electronic equipment’ (WEEE) recycling plants. Recycling of computers is usually based on a combination of manual dismantling of certain components (mainly components containing hazardous substances or valuable materials, e.g. batteries, printed circuit boards, display panels, data-storage components), followed by mechanical processing including shredding. The recycling of traditional desktop computers is perceived as non-problematic by recyclers, with the exception of some miniaturised new models (i.e. mini desktop computers), which still are not found in recycling plants and which could present some difficulties for the extraction of printed circuit boards and batteries (if present). The design of notebooks and tablets can originate some difficulties for the dismantling of batteries, especially for computers with compact design. Recycling of plastics from computers of all types is generally challenging due to the large use of different plastics with additives, such as flame retardants. According to all the interviewed recyclers, recycling of WEEE plastics with flame retardant is very poor or null with current technologies. Building on this analysis, the report then focuses on possible actions to improve material efficiency in computers, namely measures to improve (a) waste prevention, (b) repair and reuse and (c) design for recycling. The possible actions identified are listed hereinafter. (a) Waste prevention a.1 Implementation of dedicated functionality ( ) for the optimisation of the lifetime of batteries in notebooks: the lifetime of batteries could be extended by systematically implementing a preinstalled functionality on notebooks, which makes it possible to optimise the state of charge (SoC) of the battery when the device is used in grid operation (stationary). By preventing the battery remaining at full load when the notebook is in grid operation, the lifetime of batteries can be potentially extended by up to 50 %. Users could be informed about the existence and characteristics of such a functionality and the potential benefits related to its use. a.2 Decoupling external power supplies (EPS) from personal computers: the provision of information on the EPS specifications and the presence/absence of the EPS in the packaging of notebooks and tablets could facilitate the reuse by the consumer of already-available EPS with suitable characteristics. Such a measure could promote the use of common EPS across different devices, as well as the reuse of already-owned EPS. This would result in a reduction in material consumption for the production of unnecessary power supplies (and related packaging and transport) and overall a reduction of treatment of electronic waste. The International Electrotechnical Commission (IEC) technical specification (TS) 62700, the Standard Institute of Electrical and Electronics Engineers (IEEE) 1823 and Recommendation ITU-T L.1002 can be used to develop standards for the correct definition of connectors and power specifications. a.3 Provision of information about the durability of batteries: the analysis identified the existence of endurance tests suitable for the assessment of the durability of batteries in computers according to existing standards (e.g. EN 61960). The availability of information about these endurance tests could help users to get an indication on the residual capacity of the battery after a predefined number of charge/discharge cycles. Moreover, such information would allow for comparison between different products and potentially push the market towards longer-lasting batteries. a.4 Provision of information about the ‘liquid ingress protection (IP) class’ for personal computers: this can be assessed for a notebook or tablet by performing specific tests, developed according to existing standards (e.g. IEC 60529). Users can be informed about the level of protection of the computer against the ingress of liquids (e.g. dripping water or spraying water or water jets) and in this way prevent one of the most common causes of computer failure. The yearly rate of estimated material saving if dedicated functionality for the optimisation of the lifetime of batteries (a.1) were used ranges from around 2 360 to 5 400 tonnes (t) of different materials per year. About 450 t of cobalt, 100 t of lithium, 210 t of nickel and 730 t of copper could be saved every year. The estimated potential savings of materials when EPS are decoupled from notebooks and tablets (a.2) are in the range 2 300-4 600 t/year (80 % related to the notebook category, and 20 % to tablets). These values can be obtained when 10-20 % of notebooks and tablets are sold without an EPS, as users can reuse already-owned and compatible EPS. Under these conditions, for example, about 190-370 t of copper can be saved every year. This estimate may increase when the same EPS can be used for both notebooks and tablets (at the moment the assessment is based on the assumption that the two product types were kept separated). Further work is needed to assess the potential improvements thanks to the provision of information about the durability of batteries (a.3), and about the ‘liquid-IP class’ (a.4). The former option (a.3) has the potential to boost competition among battery manufacturers, resulting in more durable products. The latter option (a.4) has the potential to reduce computer damage due to liquid spillage, ranked among the most recurrent failure modes. (b) Repair/reuse b.1 and b.2 Provision of information to facilitate computer disassembly: the disassembly of relevant components (such as the display panel, keyboard, data storage, batteries, memory and internal power-supply units) plays a key role to enhance repair and reuse of personal computers. Some actions have therefore been discussed (b.1) to provide professional repair operators with documentation about the sequence of disassembly, extraction, replacement and reassembly operations needed for each relevant component of personal computers, and (b.2) to provide end-users with specific information about the disassembly and replacement of batteries in notebooks and tablets. b.3 Secure data deletion for personal computers: this is the process of deliberately, permanently and irreversibly erasing all traces of existing data from storage media, overwriting the data completely in such a way that access to the original data, or parts of them, becomes infeasible for a given level of effort. Secure data deletion is essential for the security of personal data and to allow the reuse of computers by a different user. Secure data deletion for personal computers can be ensured by means of built-in functionality. A number of existing national standards (HMG IS Standard No 5 (the United Kingdom), DIN 66399 (Germany), NIST 800-88r1 (the United States (US)) can be used as a basis to start standardisation activities on secure data deletion. The estimated potential savings of materials due to the provision of information and tools to facilitate computer disassembly were quantified in the range of 150-620 t/year for mobile computers (notebooks and tablets) within the first 2 years of use, and in the range of 610 2 460 t/year for mobile computers older than 2 years. Secure data deletion of personal computers, instead, is considered a necessary prerequisite to enhance reuse. The need to take action on this is related to policies on privacy and protection of personal data, as the General Data Protection Regulation (EU) 2016/679 and in particular its Article 25 on ‘data protection by design and by default’. Future work is needed to strengthen the analysis, however it was estimated that secure data deletion has the potential to double volume of desktop, notebook and tablet computers reused after the first useful lifetime. (c) Recyclability c.1 Provision of information to facilitate computer dismantling: computers could be designed so that crucial components for material aspects (e.g. content of hazardous substances and/or valuable materials) can be easily identified and extracted in order to be processed by means of specific recycling treatments. Design for dismantling can focus on components listed in Annex VII of the WEEE directive ( ). The ‘ease of dismantling’ can be supported by the provision of relevant information (such as a diagram of the product showing the location of the components, the content of hazardous substances, instructions on the sequence of operations needed to remove these components, including type and number of fastening techniques to be unlocked, and tool(s) required). c.2 Marking of plastic components: although all plastics are theoretically recyclable, in practice the recyclability of plastics in computers is generally low, mainly due to the large amount of different plastic components with flame retardants (FRs) and other additives. Marking of plastic components according to existing standards (e.g. ISO 11469 and ISO 1043 series) can facilitate identification and sorting of plastic components during the manual dismantling steps of the recycling. c.3 FR content: according to all the recyclers interviewed, FRs are a major barrier to plastics recycling. Current mechanical-sorting processes of shredded plastics are characterised by low efficiency, while innovative sorting systems are still at the pilot stage and have been shown to be effective only in certain cases. Therefore, the provision of information on the content of FRs in plastic components is a first step to contribute to the improvement of plastics recycling. Plastics marking (as discussed above) can contribute to the separation of plastics with FRs during the manual dismantling, allowing for their recycling at higher rates (in line with the prescription of IEC/TR 62635, 2015). However, detailed information about FRs content could be given in a more systematised way, for example through the development of specific indexes. These indexes could support recyclers in checking the use of FRs in computers and in developing future processes and technologies suitable for plastics recycling. Moreover, these indexes could support policymakers in monitoring the use of FRs in the products and, in the medium-long term, to promote products that use smaller quantities of FRs. An example of a FR content index is provided in this report. c.4 Battery marks: the identification of the chemistry type of batteries in computers is necessary in order to have efficient identification and sorting, and thus to improve the material efficiency during the recycling. It is proposed to start standardisation activities to establish standard marking symbols for batteries. The examples of the ‘battery-recycle mark’, developed by the Battery Association of Japan (BAJ), and the current standardisation activities for the IEC 62902 (standard marking symbols for batteries with a volume higher than 900 cm3) may be used as references to develop ad hoc standards. The benefits of actions for the design for recycling can be relevant. In particular, the proposed actions should contribute to increase the amounts of materials that will be recycled (6 350-8 900 t/year), in particular plastics (5 950-7 960 t/year of additional plastics), but also metals such as cobalt (55-110 t), copper (240-610 t), rare earths as neodymium and dysprosium (2 7 t) and various precious metals (gold (0.1-0.4 t), palladium (0.1-0.4 t) and silver (2 7 t)). Compared to the amount of materials recycled in the EU (2012 data), these values would represent a recycling increase of 1-2 % for cobalt, 2-5 % for palladium, and 13-50 % for rare earths.JRC.D.3-Land Resource

Artificial intelligence and decision problems: The need for an ethical context

Computers process information and make decisions. Until recently, the decisions they made were not complex, but due to the incessant technological advances that are taking place, systems based on artificial intelligence are achieving levels of competence in decision-making that in many contexts equal or surpass those of humans. These are autonomous decision-making systems that, although they can increase the capacity and efficiency of people in their fields of action, they could also replace them, something that is of concern to society as a whole. Avoiding dysfunctions in these systems is a priority social, scientific and technological objective, which requires theoretical models that include all the richness and variety of decision problems, that precisely define the elements that characterize them and that address the ethical principles that should guide their operation. This article describes each of these aspects in separate sections

Development of model based sensors for the supervision of a solar dryer

Solar dryers are increasingly used in developing countries as an alternative to drying in open air, however the inherent variability of the drying conditions during day and along year drive the need for achieving low cost sensors that would enable to characterize the drying process and to react accordingly. This paper provides three different and complementary approaches for model based sensors that make use of the psychrometric properties of the air inside the drying chamber and the temperature oscillations of the wood along day. The simplest smart sensor, Smart-1, using only two Sensirion sensors, allows to estimate the accumulated water extracted from wood along a complete drying cycle with a correlation coefficient of 0.97. Smart-2 is a model based sensor that relays on the diffusion kinetics by means of assesing temperature and relative humidity of the air inside the kiln. Smart-2 model allows to determine the diffusivity, being the average value of D for the drying cycle studied equal to 5.14 × 10−10 m2 s−1 and equal to 5.12 × 10−10 m2 s−1 for two experiments respectively. The multidistributed supervision of the dryer shows up the lack of uniformity in drying conditions supported by the wood planks located in the inner or center of the drying chamber where constant drying rate kinetics predominate. Finally, Smart-3 indicates a decreasing efficiency along the drying process from 0.9 to 0.

Cognitive load theory, educational research, and instructional design: some food for thought

Cognitive load is a theoretical notion with an increasingly central role in the educational research literature. The basic idea of cognitive load theory is that cognitive capacity in working memory is limited, so that if a learning task requires too much capacity, learning will be hampered. The recommended remedy is to design instructional systems that optimize the use of working memory capacity and avoid cognitive overload. Cognitive load theory has advanced educational research considerably and has been used to explain a large set of experimental findings. This article sets out to explore the open questions and the boundaries of cognitive load theory by identifying a number of problematic conceptual, methodological and application-related issues. It concludes by presenting a research agenda for future studies of cognitive load