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TUIs vs. GUIs : comparing the learning potential with preschoolers

TUIs vs. GUIs : comparing the learning potential with preschoolers

Limitations of the work We could not finish without referring some limitations of the study. The conclusions regarding the learning potential promoted by graphical versus tangible interfaces have to take in account the nature of the content conveyed, a physical, concrete activity. For this type of content and for the age group addressed we can say that the results of the study suggest that the physicality of the TUI has advantages over the GUI regarding its potential to provide more and long lasting engagement, which are key elements to promote learning.

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SENSORY PROCESSING DISORDER AND HIGH LEARNING POTENTIAL

SENSORY PROCESSING DISORDER AND HIGH LEARNING POTENTIAL

Sensory Processing Disorder (SPD) is the inability to use information received through the senses in order to function smoothly in daily life. SPD is not one specific disorder but an umbrella term to cover a variety of neurological disabilities. i SPD is also called Sensory Integration Dysfunction (SID). A characteristic that is common in children with high learning potential (HLP) is a heightened sensory perceptiveness. ii This fact sheet, aimed at teachers, professionals and parents/carers of children with high learning potential, will help to explain sensory processing disorder and to discern whether a child’s sensory issues need intervention. The fact sheet will cover what SPD is, how it relates to high learning potential, what treatments are available, where to find help, and how to support a HLP child with SPD at home and at school.
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The relationship between learning potential and job performance

The relationship between learning potential and job performance

The nonunionised management band of the organisation has formalised individual performance agreements (IPAs) in place that are compiled at the beginning of each year and reviewed quarterly. These IPAs include goals and objectives with targets in place for each objective set. The targets are monitored and measured quarterly and a numeral (0 – 2) is assigned for each target for the achievement or nonachievement of the plan. The Patterson bands, which were researched in this study, do not have such formalised agreements in place. These bands are unionised and all the parties concerned have struggled to provide one method of setting and measuring the targets. Once these IPAs are in place for the lower Patterson bands, this criterion measure could easily be utilised for further comparison of learning potential and job performance.
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The modification, elaboration and empirical evaluation of the De Goede learning potential structural model through the incorporation of non-cognitive learning competency potential latent variables

The modification, elaboration and empirical evaluation of the De Goede learning potential structural model through the incorporation of non-cognitive learning competency potential latent variables

70 The De Goede (2007) learning potential structural model fails to recognise the importance of motivation during learning performance as it only acknowledges the fact that cognitive abilities affect learning performance through abstract reasoning ability and information processing capacity. Cognitive ability must be considered the single best predictor of learning performance (Hunter, 1986; Hunter & Hunter, 1984; Ree & Earle, 1991; Schmidt, 2002). The research results of whether cognitive ability predicts job performance is so overwhelming that there is no doubt that this is in fact the case (Sackett, Schmitt, Ellingson, & Kabin, 2001). De Goede (2007) argues that it is extremely unlikely that cognitive ability will be the sole determinant of learning performance and suggested that an understanding of learning motivation can be a plausible additional determinant of learning performance. Pintrich and De Groot (1990) also support De Goede (2007) as they believe that knowledge of cognitive and metacognitive strategies is usually not enough to promote achievement in students, students also need to be motivated to use the strategies as well as regulate their cognition and effort (Paris, Lipson, & Wixson, 1983; Pintrich, Cross, Kozma, & Mckeachie, 1986). Students need both the “will” and „skill” to be successful in classrooms (Blumenfeld, Pintrich, Meece, & Wessels, 1982; Paris et al., 1983; Pintrich, 1989). The interaction between ability and motivation is also acknowledged in the expectancy theory of motivation. From this it seems clear that ability, in the absence of motivation, or motivation in the absence of ability is insufficient to yield performance. Colquitt et al. (2000, p. 696) found that motivation to learn explained variance in learning over and above cognitive ability and it was therefore concluded that there was „much more than g‟. Although there are classroom situations and tasks that can foster motivation (Corno & Rohrkemper, 1985; Malone, 1981), there is also evidence to suggest that students‟ perceptions of the classroom, as well as their individual motivational orientations and beliefs about learning are relevant to cognitive engagement and classroom learning performance (e.g. Ames & Archer, 1988; Nolen, 1988). Wexley and Latham (1981) add that it is widely accepted that learning and specifically transfer will only occur when trainees have both the ability and motivation to acquire and apply new skills.
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High Learning Potential Assessment

High Learning Potential Assessment

The High Learning Potential Assessment is priced at £450 for members of Potential Plus UK and £600 for non-members (£50 surcharge for weekend and school holiday assessments). The School Communication Advice pack is an op- tional extra service priced at £100 for members of Potential Plus UK and £150 for non-members. The members’ price for both the High Learning

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Development of a machine learning potential for graphene

Development of a machine learning potential for graphene

In the quantum mechanical reference data set used to generate the potential, only the total energies, forces, and virial stresses are available. In order to facilitate the simulation of systems of larger sizes than those upon which ab initio calculations are feasible, the GAP model total energy is decom- posed into a sum of local contributions, computed from kernel functions, which represent the similarity between chemical environments. In this work, we decompose the total energy function into a sum of two-body (2b), three-body (3b), and many-body (MB) interactions, which are weighted (in terms of their contribution to the total energy and atomistic forces) based on their respective statistically measured contributions. The mathematical form of these descriptors is discussed below. The largest portion of the energy is described by pairwise interactions, then 3b, then MB contributions, each of which is represented by a distinct descriptor and associated kernel function [ 45 , 46 , 53 ]. The descriptor is a transformation of the atomic Cartesian coordinates into a rotationally and transla- tionally invariant form which is suitable for use as input to a ML algorithm. Descriptors vary greatly in their complexity, the 2b term used here is simply the distance between two atoms, while the MB term takes the form of the smooth overlap of atomic positions (SOAP) descriptor, which provides an overcomplete
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Investing in Online Learning: Potential Benefits and Limitations

Investing in Online Learning: Potential Benefits and Limitations

Athabasca's MBA, but still depend heavily on print. Queen's offers an MBA through a mix of local classes and video-conferencing. As far as we know, though, there are relatively few graduate degrees offered entirely or even primarily online. This is not surprising, given that it takes several years to develop a whole masters program, and the Web is still only five or six years old, with respect to educational applications. The study findings however suggest an increasing need for such degrees. With the growth of a “knowledge society” comes the need for lifelong learning. It is interesting to note the high proportion of students in the UBC non-credit program who already had higher degree qualifications, but still felt the need to up-date their skills.
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Hybrid Learning in Higher Education: The Potential of Teaching and Learning with Robot-Mediated Communication

Hybrid Learning in Higher Education: The Potential of Teaching and Learning with Robot-Mediated Communication

In a recent publication in Online Learning, Whiteside (2015) proposed a framework for social presence that suggested that class community and emotional connection are critical components of this construct. Other theoretical frameworks for social presence (Biocca, Harms, & Burgoon, 2003) describe it as comprised of 1) co-presence, 2) psychological involvement, and 3) behavioral engagement. Co-presence involves students being aware of each other and feeling like they are in the same place. Psychological involvement exists when students are engaged in student-student and instructor-student interactions and there is mutual understanding. Behavioral engagement can involve “eye contact, nonverbal mirroring, turn taking, and so forth” (Biocca et al., 2003, p. 465). Some researchers have argued that social presence is a necessary precondition for learning to occur, especially collaborative and social learning (So & Brush, 2008); others have argued that social presence is a by-product of an effective collaborative learning environment (Bower, Delgarno, Kennedy, Lee, & Kenney, 2015). Taken together, these ideas suggest that high social presence is facilitated in learning environments where all students feel included, seen, heard, respected and “valued as people, not merely an image on a display or a body in a seat” (Bell et al, 2016, p. 20). Attending to social presence is important because (both online and offline) students’ abilities to establish relationships with faculty and with other students have a direct and significant effect on their level of scholarly engagement and learning outcomes (Kuh, Cruce, Shoup, Kinzie, & Gonyea, 2008).
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An Analysis of the Educational Potential of Augmented Reality Games for Learning

An Analysis of the Educational Potential of Augmented Reality Games for Learning

In order to reduce such complexities in the pattern approach, further research on the correlations between patterns and learning outcomes has to focus on a limited number of the patterns in existence (cf. Björk and Holopainen, 2004; Davidsson et al., 2004). The study settings have to comprise (a) an experimental variation of patterns, i.e. game settings that enable/disable individual patterns and (b) an in-depth variation of patterns, i.e. game settings that allow different instances for the same pattern. This way, measurable and feasible results can be obtained that are suitable as a base for design guidelines which define (a) patterns that support the achievement of a desired learning outcome and (b) ways of applying the patterns. Future research needs to verify the effectiveness of mobile learning games and to corroborate their educational value in order to motivate teachers to use such tools for teaching. Otherwise, the educational system may run the risk of disengaging future learners (Klopfer et al., 2011).
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Machine learning a general purpose interatomic potential for silicon

Machine learning a general purpose interatomic potential for silicon

Several point defects are represented in the fitting data- base (Table I), and their formation energies would therefore be expected to be accurately reproduced by the GAP. Indeed, as Fig. 1 shows, the relative error for the vacancy and three interstitial positions, hexagonal, tetrahedral, and dumbbell, are all within at most 7% of the reference DFT values. The only other potential that is close to this level of accuracy is EDIP, with similar errors for all but the hexagonal interstitial, where it is off by 14%. All the other potentials, as well as DFTB, differ from our DFT calcu- lations by tens of percent for at least some of the defects. Since point defects control properties such as diffusivity in bulk silicon, their migration barriers are also of interest and as they represent bond breaking and formation proc- esses, often present a challenge for interatomic potentials. Since the training database configurations come from finite-temperature MD, it could, in principle, include configurations near the barrier, but, since the system spends relatively little time near the energy saddle point, this is actually unlikely [52]. However, the hexagonal and tetra- hedral interstitials are related by a short displacement, so one is typically a local minimum and the other a saddle point along an interstitial diffusion pathway. We find that the GAP preserves the DFT ordering, although the energy difference is underestimated, while the other potentials make much larger errors, many reversing the relative order of the two high-symmetry geometries. Two other related observables, the migration path of the vacancy and the formation energy of the fourfold defect [193] (the midpoint of the concerted-exchange diffusion mechanism [194,195]), which are not represented in the database, are discussed below in Secs. IV E and IV F.
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Learning to Escape: Prison Education, Rehabilitation and the Potential for Transformation

Learning to Escape: Prison Education, Rehabilitation and the Potential for Transformation

The rigidity of the daily routine is central to impris- onment. Robert McCleery (1961, p.154) pointed out that “the heart of custodial controls in traditional pris- ons lies in the daily regimentation, routine and rituals of domination which bend the subjects into a customary posture of silent awe and unthinking acceptance.” While the extent to which prisoners are bent into com- pliance may be exaggerated, the general point about the corrosive effect of routine is well made. Critical think- ing can only develop when we accept that the process will be uncomfortable, ambiguous, tentative, uncertain and evolving (Brookfield, 1987). However, prisons have a tendency to create regimes where prisoners can “find the maintenance of behavioural boundaries satis- fying, because it implies exemption from difficult choices and personal responsibility for one’s plight” (Mathiesen, 1996, p.371). Ironically, the lack of responsibility provides safety in the comfort zone. There is little opportunity for ambiguity, uncertainty or feelings of insecurity in such a stifling routine. The process of transforming frames of reference begins with critical reflection, with assessing one’s own as- sumptions and presuppositions. To engage in critical reflection usually leaves one uncomfortable and chal- lenged (Mezirow, 1996). It seems that traditional prison regimes create an environment that must work against this. Regime and routine can undermine the potential to put students in an uncomfortable place where they have the space and support that Kirk suggest is needed for the process of change and transformation.
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Potential Impact of Blended Learning on Teacher Education in Mongolia

Potential Impact of Blended Learning on Teacher Education in Mongolia

This study examined the potentials of blended learning to achieve better quality in higher education. Blended learning class students had high satisfaction be- cause of reasons such as more acquired skills, more independent study and col- laboration, more flexibility and more opportunities to review before face-to-face classes. Results show that blended class could achieve better grades than tradi- tional class, with higher proportion of the students with satisfactory grade. Stu- dents expressed that they would like more blended courses in the future, despite concerns about laboratory and network environment. The instructor time was used more efficiently and she feels that students acquired more skills in the blended class.
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Unlocking Potential for Learning

Unlocking Potential for Learning

The next strategic area is Developing Precision in Knowledge, Skills, and Daily Practices for Improving Learning. This involves three key components. One component is attention to capacity building to extend professional learning, particularly in the areas of literacy and numeracy instruction, assessment for learning, classroom management, and instructional leadership. A second component is careful attention to curriculum development, instruction, and interventions to improve teaching and learning for all students system-wide and within schools. The third component is the regular use and understanding of data at the system and school level and the development of assessment literacy within schools to ensure instruction is informed by data about student learning and progress. The final strategic area is Sharing Responsibility through Building Partnerships. This involves two key components. First is the fostering of partnerships within the system, for example, between central office and schools and across schools, and with parents, communities, and other organizations and agencies to build shared involvement in, and responsibilities for, supporting student learning. This requires the second component of clear communication, where a consistent message about raising student achievement is communicated widely, frequently, and with a sense of urgency.
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Children’s Questions in Science Classrooms: A Potential Source of Learning

Children’s Questions in Science Classrooms: A Potential Source of Learning

There are several obstacles like children’s knowledge of different types and levels of questions, the teacher-pupil interaction and teachers’ attitude towards children’s questions that may prevent children from asking questions in the classroom. Furthermore, there is individual differences in children too; some raise questions easily, while for other’s it becomes a difficult task. This difference may depend on the individual’s predisposition to taking risks, learning style and ability to tolerate uncertainty (Meij et al. 1994). Some children try to clear their doubts immediately, while other sustain their doubt just to avoid explicit questioning. They may be anxious about what if their question is silly, what if other children make fun of them. Such thoughts discourage them for asking questions. They feel that they are avoiding public embarrassment, or ridicule.
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Augmented  Learning  with  Errors:  The  Untapped  Potential  of  the  Error  Term

Augmented Learning with Errors: The Untapped Potential of the Error Term

Abstract. The Learning with Errors (LWE) problem has gained a lot of attention in recent years leading to a series of new cryptographic applications. Specically, it states that it is hard to distinguish random linear equations disguised by some small error from truly random ones. Interestingly, cryptographic primitives based on LWE often do not exploit the full potential of the error term beside of its importance for security. To this end, we introduce a novel LWE-close assumption, namely Augmented Learning with Errors (A- LWE), which allows to hide auxiliary data injected into the error term by a technique that we call message embedding. In particular, it enables existing cryptosystems to strongly increase the message throughput per ciphertext. We show that A-LWE is for certain instantiations at least as hard as the LWE problem. This inherently leads to new cryptographic constructions providing high data load encryption and customized security properties as required, for instance, in economic environments such as stock markets resp. for nancial transactions. The security of those constructions basically stems from the hardness to solve the A-LWE problem.
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Realizing the Potential of Mobile Phone Technology for Language Learning

Realizing the Potential of Mobile Phone Technology for Language Learning

Though despairingly referred to as “dumb phones”, in the hands of a smart programmer, such Java-enabled, multimedia, memory enhanced devices are capable of a great deal more functionality than is generally recognized. Given the MobLang target audience, the choice of mobile phone platform fairly well imposed itself. Although our pilot testing is restricted to Nokia (6303i), MobLang lessons have the potential to run on any Java-enabled phone equipped with a mico-SD memory card and capable of audio recording.

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Machine learning in estimating of SMEs investment potential in Ukraine

Machine learning in estimating of SMEs investment potential in Ukraine

2 Literature Review The potential as a scientific category is universal in application. This allows it to be used in various fields of science: in biology, mathematics, physics, medicine and eco- nomics (particularly in investment). In economics investment, innovative, personnel, financial, technical potentials have been described in different literature studies. In this research investment potential of SMEs has been considered because it determines the directions of their activity at the investment market. It forms the grounds for further investment. Investment potential defines the axis, strategy, and performance of SMEs. Investment potential at the macro level shows potential volumes of attraction of finan- cial resources to investment processes, revealing the contribution of SMEs to the coun- try's economic growth. Permanent monitoring and measurement of the investment po- tential of SMEs allows their investment activity and their investment preferences to be tracked, and to determine the problems of feasibility of using resources for further in- vestment.
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Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential

Global mapping of potential natural vegetation: an assessment of machine learning algorithms for estimating land potential

Potential natural vegetation (PNV) is the vegetation cover in equilibrium with climate, that would exist at a given location if not impacted by human activities. PNV is useful for raising public awareness about land degradation and for estimating land potential. This paper presents results of assessing machine learning algorithms—neural networks (nnet package), random forest (ranger), gradient boosting (gbm), K-nearest neighborhood (class) and Cubist—for operational mapping of PNV. Three case studies were considered: (1) global distribution of biomes based on the BIOME 6000 data set (8,057 modern pollen-based site reconstructions), (2) distribution of forest tree taxa in Europe based on detailed occurrence records (1,546,435 ground observations), and (3) global monthly fraction of absorbed photosynthetically active radiation (FAPAR) values (30,301 randomly-sampled points). A stack of 160 global maps representing biophysical conditions over land, including atmospheric, climatic, relief, and lithologic variables, were used as explanatory variables. The overall results indicate that random forest gives the overall best performance. The highest accuracy for predicting BIOME 6000 classes (20) was estimated to be between 33% (with spatial cross-validation) and 68% (simple random sub-setting), with the most important predictors being total annual precipitation, monthly temperatures, and bioclimatic layers. Predicting forest tree species (73) resulted in mapping accuracy of 25%, with the most important predictors being monthly cloud fraction, mean annual and monthly temperatures, and elevation. Regression models for FAPAR (monthly images) gave an R-square of 90% with the most important predictors being total annual precipitation, monthly cloud fraction, CHELSA bioclimatic layers, and month of the year, respectively. Further developments of PNV mapping could include using all GBIF records to map the global distribution of plant species at different taxonomic levels.
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The Potential Benefits of Japanese MMORPGs for Japanese Learning Motivation

The Potential Benefits of Japanese MMORPGs for Japanese Learning Motivation

Strachan, Montgomery, and Pickard (2011) looked at the influence of Massively Multiplayer Online Role-playing Games (MMORPGs) on students’ attitudes towards English as a second language (ESL) learning and the language development of those students. Results showed that playing games significantly increased students’ motivation as well as language skills in reading, speaking, listening, and writing. Another longitudinal study (Lee & Gerber, 2013) studying a gamer who played World of Warcraft found that as an ESL player became more and more into the game, his awareness of English increased while frequently interacting with English native speakers. As a result, he learned more language expressions. As all of the above studies were looking at MMORPGs in particular, these results suggested that this environment had unique characteristics that could potentially benefit foreign language performances and motivation.
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Scandinavian students’ perspective on learning from digital learning environment: The potential role of interactive quality

Scandinavian students’ perspective on learning from digital learning environment: The potential role of interactive quality

This research aims to identify the role of interactive quality to assess the Scandinavian students’ perceived learning from the digital learning environment. The quantitative research methodology is used by utilizing the questionnaire as a survey tool by targeting the Scandinavian students who are using digital learning environment. The findings show that socialability based interactivity significantly influence the students’ learning. The future directions and contributions are discussed in the concluding section.

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