Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Aquilegia, Vol. 28 No. 2, March-April 2004: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1111/thumbnail.jp

A model for the creation of human-generated metadata within communities

This paper considers situations for which detailed metadata descriptions of learning resources are necessary, and focuses on human generation of such metadata. It describes a model which facilitates human production of good quality metadata by the development and use of structured vocabularies. Using examples, this model is applied to single and multiple communities of metadata creators. The approach for transferring vocabularies across communities is related to similar work on the use of ontologies to support the development of the semantic web. Notable conclusions from this work are the need to encourage collaboration between the metadata specialists, content authors and system designers, and the scope for using accurate and consistent metadata created for one context in another context by producing descriptions of the relationships between those contexts

Collaborative trails in e-learning environments

This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

Sled-Pull Training Protocol Increases Critical Speed in Female Collegiate Soccer Players

Critical speed (CS) is the speed one can sustain while maintaining blood lactate, phosphocreatine, and oxygen uptake levels. “Distance capacity beyond CS” (D’) is the reserve an athlete can draw from to run faster than their CS. By increasing CS and D’, athletes can sustain a faster threshold pace (CS) and have a greater sprint capacity (D’). Unlike distance traveled and speed, which do not reflect the metabolic strain of an exercise, CS and D’ assess the relative intensity of an activity to provide individualized inter- and intra-competition insight. PURPOSE: This investigation evaluated CS and D’ among men and women Division I collegiate soccer players for the first time and assessed the efficacy of a 12-week sled-pulling program intended to improve their CS profiles. METHODS: Using a 3-minute all-out 25-meter shuttle run, the speed of the first 150s (S’150), CS, and D’ of 23 men (20.22 ± 1.53 years, 168.28 ± 51.17 cm, 73.44 ± 23.46 kg) and 17 women (19.58 ± 1.02 years, 167.07 ± 3.81 cm, 62.46 ± 8.41 kg) was assessed before and after the training protocol. Video analysis was used to track displacement over time. RESULTS: The training program increased the S’150 of men by 3.58% (3.66 ±0.19 vs 3.77 ± 0.17 m/s, pCONCLUSION: Sled-pull training improved the CS profile of both men and women. Additional research is necessary to determine how improvements in S’150 and CS translate to better performance in competition

Sled Pull Training Protocol Does Not Improve Peak Force and Increases Asymmetry in Collegiate Soccer Players

Speed and acceleration are trainable components that are critical determinants of success in team sports, particularly soccer. Lower extremity strength is one of many factors that determine the maximal force output and velocity of individuals, which is critical to success in sport. PURPOSE: To determine the effects of a 12-week sled pull training intervention on isometric leg strength and asymmetry. METHODS: Participants from Division 1 collegiate men (20 ± 1.5yrs, 168.28 ± 51.17cm, 73.44 ± 23.46kg) and women’s soccer (19.58 ± 1.02yrs, 167.07 ± 3.81cm, 62.46 ± 8.41kg) team performed pre-training isometric thigh pulls on force plates measuring peak force generation, bilaterally. Participants then performed a 12-week training program consisting of sled pulls performed at 80% of bodyweight, three days a week for 6 weeks followed by a 6-week maintenance phase of sled pulls conducted at 50% of bodyweight and post-intervention testing. RESULTS: The pre-training average relative peak force of the left and right legs of male participants were 14.46 ± 1.61N/kg and 14.42 ± 1.33N/kg, respectively, and 11.76 ± 0.69N/kg and 11.67 ± 1.08N/kg, respectively, of female participants. Sled pull training trended (p=0.07) to increase relative peak force in the right leg in both men (15.11 ± 2.14N/kg) and women (12.27 ± 1.31N/kg). However, training trended (p=0.09) to decrease peak left leg force in both men (13.60±2.32N/kg), but less so in women (11.19 ± 1.77N/kg). This leg specific training effect increased (pCONCLUSION: Sled pull training increased asymmetry in both men and women. The increased asymmetry could be attributed to a consistent decline in unilateral force production in the left leg in men. However, there was no consistent pattern to explain the increased asymmetry in women

Sled-pull Training Improves Maximal Horizontal Velocity in Collegiate Male and Female Soccer Players

The force velocity profile (FvP), which details the capacity to sprint and accelerate, is a determinant of success in soccer. To date, no data exist that details the FvP of male and female collegiate Division I soccer players. Further, there is limited insight on how training interventions may modify the FvP of either males or females. PURPOSE: The aim of this investigation was to compare FvP between collegiate male and female athletes and assess the efficacy of a 12-week sled pull training intervention. METHODS: 17 male (20.17 ± 1.38 yrs) and 12 female (19.75 ± 1.05 yrs) soccer players participated in a 12-week sled pull training intervention. FvP was measured prior, during, and after training using a 30m sprint to assess maximal horizontal force (F0), maximal horizontal speed (V0), and maximal power output (Pmax). RESULTS: The intervention improved 30m sprint times of men by 11.86% (pre: 4.35 ± 0.17s, post: 4.27 ± 0.17, p0 in both men (pre: 7.98 ± 0.36 m/s, post: 8.09 ± 0.35 m/s, p0 or Pmax. CONCLUSION: This is the first study to detail FvP in both male and female collegiate soccer players. A 12-week sled pull training intervention improves 30m sprint times and V0 in both male and female collegiate athletes, but does not improve F0 and Pmax. Thus, the sled pull intervention should be modified or paired with other training that specifically targets force and power development

Personalised trails and learner profiling in an e-learning environment

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Analytical study of non-linear transport across a semiconductor-metal junction

In this paper we study analytically a one-dimensional model for a semiconductor-metal junction. We study the formation of Tamm states and how they evolve when the semi-infinite semiconductor and metal are coupled together. The non-linear current, as a function of the bias voltage, is studied using the non-equilibrium Green's function method and the density matrix of the interface is given. The electronic occupation of the sites defining the interface has strong non-linearities as function of the bias voltage due to strong resonances present in the Green's functions of the junction sites. The surface Green's function is computed analytically by solving a quadratic matrix equation, which does not require adding a small imaginary constant to the energy. The wave function for the surface states is given