Condtional Expectation of Order Statistic

Question

Given a a random sample $X_1, X_2, X_3, X_4$ and family of densities $\mathcal{P} = \left\{ f_\theta: \theta \in \Theta \right\}$, where $f_\theta(x) = \frac{1}{2}\mathbb{I}_{[\theta-1, \theta + 1]}$, we can estimate $\theta$ by $\hat{\theta} = X_{(2)} + \frac{1}{5}$. Now we also know that $(S, T)= (X_{(1)}, X_{(4)})$ is a sufficient statistic for $\theta$ so we may Rao-Blackwellize our estimator: $$ \hat{\theta}^*= \mathbb{E}(\hat{\theta}|(X_{(1)},X_{(4)})) = \mathbb{E}(X_{(2)}|(X_{(1)},X_{(4)})) + \frac{1}{5}.$$ Unfortunately I haven't been able to compute the last conditional expectation. Any input would be greatly appreciated! :)