A comparison of A-level performance in economics and business studies: how much more difficult is economics?

This paper uses ALIS data to compare academic performance in two subjects often viewed as relatively close substitutes for one another at A-level. The important role of GCSE achievement is confirmed for both subjects. There is evidence of strong gender effects and variation in outcomes across Examination Boards. A counterfactual exercise suggests that if the sample of Business Studies candidates had studied Economics nearly 40% of those who obtained a grade C or better in the former subject would not have done so in the latter. The opposite exercise uggests that 12% more Economics candidates would have achieved a grade C or better if they had taken Business Studies. In order to render a Business Studies A-level grade comparable to an Economics one in terms of relative difficulty, we estimate that a downward adjustment of 1.5 UCAS points should be applied to the former subject. This adjustment is lower than that suggested by correction factors based on conventional subject pair analysis for these two subjects

Band alignments at Ga₂O₃ heterojunction interfaces with Si and Ge

Amorphous Ga2O3 thin films were deposited on p-type (111) and (100) surfaces of silicon and (100) germanium by atomic layer deposition (ALD). X-ray photoelectron spectroscopy (XPS) was used to investigate the band alignments at the interfaces using the Kraut Method. The valence band offsets were determined to be 3.49± 0.08 eV and 3.47± 0.08 eV with Si(111) and Si(100) respectively and 3.51eV± 0.08 eV with Ge(100). Inverse photoemission spectroscopy (IPES) was used to investigate the conduction band of a thick Ga2O3 film and the band gap of the film was determined to be 4.63±0.14 eV. The conduction band offsets were found to be 0.03 eV and 0.05eV with Si(111) and Si(100) respectively, and 0.45eV with Ge(100). The results indicate that the heterojunctions of Ga2O3 with Si(100), Si(111) and Ge(100) are all type I heterojunctions

Low temperature growth and optical properties of alpha-Ga2O3 deposited on sapphire by plasma enhanced atomic layer deposition

Plasma enhanced atomic layer deposition was used to deposit thin films of Ga2O3 on to c-plane sapphire substrates using triethylgallium and O2 plasma. The influence of substrate temperature and plasma processing parameters on the resultant crystallinity and optical properties of the Ga2O3 films were investigated. The deposition temperature was found to have a significant effect on the film crystallinity. At temperatures below 200°C amorphous Ga2O3 films were deposited. Between 250°C and 350°C the films became predominantly α-Ga2O3. Above 350°C the deposited films showed a mixture of α-Ga2O3 and ε-Ga2O3 phases. Plasma power and O2 flow rate were observed to have less influence over the resultant phases present in the films. However, both parameters could be tuned to alter the strain of the film. Ultraviolet transmittance measurements on the Ga2O3 films showed that the bandgaps ranges from 5.0 eV to 5.2 eV with the largest bandgap of 5.2 eV occurring for the α-Ga2O3 phase deposited at 250°C

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used