Interaction design guidelines 3.2 Critiquing aid After recommended items are computed and displayed to the user, the critical concern now should be how to aid users in providing critiques to the item. As introduced before, there are principally two types of critiquing aids: the sys stem suggested critiquing approach that generates and proposes a limited set of critiques for users to select, and the user-initiated critiquing approach that does not offer pre- tiques, but allow ws users to create and compose critiques on their own. The user-initiated method is more flexible to support various critique forms. For example, in the Example Critiquing interface, users can choose to make similarity-based tiquing(e.g, "find some cameras similar to this one"), quality-based(e. g,"find a similar camera, but cheaper") or even quantity-based(e. g, "find something similar to this camera, but at least $100 cheaper"). However, the system-suggested critiquin approach is limited in this respect given that it is the system to determine the form. not the user. In fact, FindMe and Dynamic Critiquing only suggest quality-based cri- jues(e.g, "cheaper, ""bigger, " or"Different Manufacture, Lower Resolution and Cheaper) which were viewed as a compromise between the detail provided by value elicitation and the ease of feedback associated with preference-based methods(Smyth and McGinty 2003; McCarthy et al. 2005c) In reference to the Dynamic Critiquing interface, the critiquing aid can contain two sub-components: unit critiquing(on a single feature)and compound critiquing (on multiple features simultaneously) which are respectively termed UC and Cc in the following content. Each sub-component can be in either system-suggested or user initiated style. For example, the UC in FindMe(Burke et al. 1997)is system-suggested (e. g,"cheaper","bigger"), whereas in DynamicCritiquing, it is more user-initiated since users can choose which feature to critique and how to critique it. The CC support owever, is purely system-suggested because a limited set of compound critiques is proposed for users to select(usually three suggestions as shown in Fig. 2) In the Example Critiquing interface, both UC and CC are supported in the user initiated way. Specifically, the user can improve or compromise one feature at a time and leave the others unchanged (i.e, unit critique), or combine any set of unit critiques nto a compound critique Therefore, considering the degree of user control, the user-initiated method should llow for a higher level given that the control is largely in the hands of users, relative to the system-suggested critiquing approach where users can only""select", not"create However, it is hard to assert which method would certainly perform better in improving on real-users' decision performance and subjective attitudes Table I lists all of the discussed variables, with Dynamic Critiquing and Example 4 User evaluation framework le have conducted a series of three user trials. in order to understand the effect of these ariables on users' actual decision behavior and subjective perceptions. The first trialInteraction design guidelines 177 3.2 Critiquing aid After recommended items are computed and displayed to the user, the critical concern now should be how to aid users in providing critiques to the item. As introduced before, there are principally two types of critiquing aids: the system￾suggested critiquing approach that generates and proposes a limited set of critiques for users to select, and the user-initiated critiquing approach that does not offer pre￾computed critiques, but allows users to create and compose critiques on their own. The user-initiated method is more flexible to support various critique forms. For example, in the ExampleCritiquing interface, users can choose to make similarity-based cri￾tiquing (e.g., “find some cameras similar to this one”), quality-based (e.g., “find a similar camera, but cheaper”) or even quantity-based (e.g., “find something similar to this camera, but at least $100 cheaper”). However, the system-suggested critiquing approach is limited in this respect given that it is the system to determine the form, not the user. In fact, FindMe and DynamicCritiquing only suggest quality-based cri￾tiques (e.g., “cheaper,” “bigger,” or “Different Manufacture, Lower Resolution and Cheaper”) which were viewed as a compromise between the detail provided by value elicitation and the ease of feedback associated with preference-based methods (Smyth and McGinty 2003; McCarthy et al. 2005c). In reference to the DynamicCritiquing interface, the critiquing aid can contain two sub-components: unit critiquing (on a single feature) and compound critiquing (on multiple features simultaneously) which are respectively termed UC and CC in the following content. Each sub-component can be in either system-suggested or user￾initiated style. For example, the UC in FindMe (Burke et al. 1997) is system-suggested (e.g., “cheaper”, “bigger”), whereas in DynamicCritiquing, it is more user-initiated since users can choose which feature to critique and how to critique it. The CC support in DynamicCritiquing, however, is purely system-suggested because a limited set of compound critiques is proposed for users to select (usually three suggestions as shown in Fig. 2). In the ExampleCritiquing interface, both UC and CC are supported in the user￾initiated way. Specifically, the user can improve or compromise one feature at a time and leave the others unchanged (i.e., unit critique), or combine any set of unit critiques into a compound critique. Therefore, considering the degree of user control, the user-initiated method should allow for a higher level given that the control is largely in the hands of users, relative to the system-suggested critiquing approach where users can only “select”, not “create”. However, it is hard to assert which method would certainly perform better in improving on real-users’ decision performance and subjective attitudes. Table 1 lists all of the discussed variables, with DynamicCritiquing and Example￾Critiquing as examples to see their typical values. 4 User evaluation framework We have conducted a series of three user trials, in order to understand the effect of these variables on users’ actual decision behavior and subjective perceptions. The first trial 123