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Convenience sampling is a non-probability sampling technique where samples are selected based on their easy availability and proximity to the researcher. It's often used in exploratory research and the earliest phases of research projects. The primary advantage of convenience sampling is its simplicity and speed. However, this comes with a trade-off in the area of accuracy and representation.

In the context of the given exercise, the researchers selected students from a psychology class at a small, competitive college. These students were conveniently located at the research site, making it easier for the researchers to collect data. This choice is understandable in terms of logistics, but it introduces significant biases.

The main issue with convenience sampling is that it doesn't provide a mechanism to generalize findings to a larger population. The sample lacks randomness and diversity, especially if demographic or other contextual factors greatly vary in the broader population. Therefore, any insights derived from a convenience sample should be considered with caution, as they may not reflect broader trends.

Generalization is the process of applying findings from a sample to a broader population. However, when this process involves a convenience sample like in the exercise, significant limitations arise. Generalization limitations become a concern because the specific sample might not adequately capture the diversity of the whole population.

In the case of the surveyed students from a particular psychology class, findings cannot be generalized to all U.S college students. Firstly, because those surveyed all belonged to a single academic discipline, insights from this group may not apply to students in different fields of study who may have different study habits, stress levels, or availability and exposure to stimulants.

Moreover, the college's competitive nature may also skew results, as students in other less competitive institutions may face different academic pressures and environmental influences. These factors are critical since they can significantly alter the kinds of conclusions that one might draw about stimulant use among college students nation-wide.

A representative sample is one that accurately reflects the various characteristics of the whole population, thereby allowing researchers to generalize their findings broadly. When a sample is not representative, like with convenience sampling, systematic inaccuracies can occur.

For a sample to be representative, it must be randomly selected with every member of the population having a known chance of being included. Incorporating techniques such as stratified sampling or systematic sampling can help ensure this randomness.

In the discussed exercise, because the sample was limited to a small, competitive college's psychology students, it was not representative of the entire U.S. college student population. A more representative approach would involve sampling students across different universities, disciplines, and varying levels of competitiveness. Only then can one more confidently extrapolate findings to a wider college demographic, reducing bias and increasing the credibility of generalized conclusions.