Reflejo de las deformaciones en los espectros Raman.

Psychometric measures focussing on the tenets of SDT, generally encompass multiple, broad constructs such as intrinsic motivation, extrinsic motivation and amotivation. From these measures subscales can be differentially summed to assess levels of autonomy and self- determination (Hart et al. 2007; Faye and Sharpe 2008; Ullrich-French and Cox 2009;

Vansteenkiste et al. 2009). Amalgamating subscales into broader categories may result in some of the raw subscale data (e.g. intrinsic motivation to know, extrinsic motivation for introjected regulation) being hidden from the final analysis (Faye and Sharpe 2008). Also averaging situational motivation data over a period of time in order to report contextual motivation would obscure actual motivational changes within each situation. However, adopting an additive approach, such as when calculating the quality and quantity of motivation, rather than using averages may highlight important aspects of motivation or motivational change within activity (Ullrich-French and Cox 2009; Vansteenkiste et al. 2009).

Some research has utilised a self-determination index (SDI) rating to explain motivational differences across activities. This method used to calculate the SDI, relies on application of weightings for some subscales and then subtracting one motivation score from another. The equation would look like: [(2 x intrinsic motivation) + (identified regulation) – (introjected regulation) – (2 x external regulation)] (Standage et al. 2006; Ullrich-French and Cox 2009). These methods of calculating motivation data have been used mainly on the Sports Motivation Scale (SMS; Pelletier et al. 1995), although other scales designed to measure self-determined motivation (e.g. Academic Motivation Scale; AMS-C 28 Vallerand and Pelletier 1992) utilising the principles from SDT have used similar calculations to assess contextual motivation.

The Sports Motivation Scale (SMS; Pelletier et al. 1995) is a commonly used measure which assesses intrinsic motivation, extrinsic motivation and amotivation at a contextual level of generality, according to the HMIEM. The SMS does not pre-empt a specific intrinsic or extrinsic orientation but instead appraises the individual’s motives for the activity in which the individual usually participates (Shaw et al. 2005; Beaudoin 2006). There is some discussion in the literature concerning items on the three intrinsic motivation subscales, suggesting these subscales are not differentiated enough and could be amalgamated into one subscale (Martens

42

and Webber 2002; Shaw et al. 2005; Mallet et al. 2007). However, SDT defines intrinsic motivation differently for each of the three categories; intrinsic motivation to know, to accomplish and to experience stimulation (Deci and Ryan 2000; 2008). Therefore, combining these constructs could lead to a misinterpretation of intrinsic motives.

Further problems with the SMS were revealed in a study for Masters’ athletes where some of the amotivation items loaded onto intrinsic motivation subscales but were interpreted as

reflecting the athletes’ uncertainty about continued participation at such a high level (Shaw et al. 2005). This loading of amotivation on to some intrinsic motivation subscales may be indicative of the complex associations and interactions between hierarchical levels (Wilson et al. 2003), or due in part to the subtle differences in defining some intrinsic and extrinsic constructs.

However, this loading effect may be due to the timing of the measure. The Master’s athletes completed the SMS whilst they were attending a competition thus the progress towards their goals at the time of completion may have been in different stages for each athlete thereby influencing their responses to the SMS (Shaw et al. 2005). Despite some discrepancies within the literature, the SMS is still accepted as a valid measure assessing motivation at the contextual level of generality (Martens and Webber 2002).

Additionally, through the development of the hierarchical model of intrinsic and extrinsic motivation, Guay et al. (2000) developed a situational measure of motivation called the Situational Motivational Scale (SIMS; Guay et al. 2000). The SIMS adopts an amalgamated subscale for intrinsic motivation, citing the necessity for reduced items, and omits the

introjection subscale. This process of reduction results in a 16-item measure including intrinsic motivation, extrinsic motivation for identified regulation, extrinsic motivation for external regulation and amotivation subscales (Guay et al. 2000). Further analysis of the SIMS by Standage et al. (2003) suggests that motivation at the situational level uses complex and diverse processes which may not be fully explained solely through a general measure of motivation. However, whilst the SIMS is a specific situational measure of motivation and because situational motivation has not been the main focus of motivational research, there is little evidence that this measure assess situational motivation accurately.

Many authors agree that the measurement of situational motivation should occur longitudinally within the activity, to assess trends and changes in motivation (Kavussanu and Roberts 1996; Gernigon et al. 2004; Hein and Hagger 2007; Standage et al. 2008). This repeated measurement is shown to be effective in enhancing reliability of data, particularly where more than one

43

instrument was used to measure the same construct (Steyer et al. 1999; Deponte 2004). Situational variables and the ensuing influence on the individual can complicate the

measurement process, as individuals actively seek out situational cues to confirm or dispute current cognitive and emotional states (Lu 1999). It could be argued that all measurement is situational by nature as it is collected in situations at a single point in time, thus results are also influenced by the effects of the situation on the person at the time of measurement (De Raad and Schouwenburg 1996; Steyer et al. 1999). However, Judge and Ilies (2002) suggest that in order to gain a high level of validity, global measures should be taken in a cross-sectional manner as the situational approach may include too much error at each point of measurement.

Furthermore, ascertaining motivational change over time and attributing this to specific reasons or events is complex and may lead to more confusion and contradiction (Baird et al. 2006). In addressing this difficulty for situational measurement, this thesis will firstly identify important situational factors which could be considered to influence situational motivation and then explore the processes of how these factors interact with motivation at the situational level.